Free, for real
No subscription, no credits, no 1102tools sign-up. MIT-licensed code you can read, run, and fork.
FEDERAL CONTRACTING · FREE · OPEN SOURCE
Free MCP servers connect your AI to federal data. These prompts help you ask useful questions about opportunities, awards, teaming, pricing, and regulations. Install and connect the required MCPs in your AI client before using a prompt.
IN THE CLAUDE DIRECTORYIN THE CHATGPT DIRECTORY
Three real market research questions, answered live from USAspending.gov.
SAM.gov · USAspending · GSA CALC+ · BLS OEWS · GSA Per Diem · eCFR · Federal Register · Regulations.gov · Acquisition.gov
WHY 1102TOOLS
Commercial GovCon platforms add capture and proposal workflows, and most charge for AI or MCP access. 1102tools costs nothing, needs no 1102tools account, and publishes the testing record behind every server.
No subscription, no credits, no 1102tools sign-up. MIT-licensed code you can read, run, and fork.
Each server is checked against its government source. Its repository records what was tested, found and fixed.
Nine servers in Claude's directory. Six servers in ChatGPT's directory. The rest are planned for ChatGPT. Directory installs need no 1102tools account and no user API key. Other apps' free tiers and account requirements vary.
Each server's tests rerun every week on the newest MCP SDK, and hosted services are health-checked every 30 minutes.
The only known MCP server for Acquisition.gov FAR Overhaul model text and agency class deviations.
HOW EVERY SERVER IS TESTED
More free tools for contracting professionals: KTHQ ↗
LOCAL OR HOSTED
Every MCP works both ways. Local runs it on your computer, inside the Claude or ChatGPT desktop app. Hosted runs it on Cloudflare, so it works anywhere you use Claude or ChatGPT. Local is the better setup for daily work.
Claude or ChatGPT, on your computer
Your own full rate limits, so you skip any congestion on hosted.
Claude or ChatGPT desktop apps and other AI apps, on a desktop or laptop
Ask your AI to set it up from the setup guide. Free keys for SAM.gov, Regulations.gov, and GSA Per Diem
Your own, in full
Government sources
Manual. Local installs don't update themselves. Ask your AI to update them
Full edition: 20 tools, free key
Claude or ChatGPT, anywhere
Always up to date. No keys, and it works in Claude or ChatGPT anywhere.
Claude or ChatGPT on web, desktop, and phone
Install from the Claude or ChatGPT directory. No keys
Pooled across all users. Your lookups stay private
Government sources and Cloudflare
Automatic. Always runs the latest release
6 tools, no key
Use hosted if you're on your phone, your work computer blocks installs, or you want SAM.gov opportunity, public registration, or exclusion research without a key.
A SIMPLE WAY TO START
Find a prompt below. Its source labels show which MCPs it needs.
Set up the required MCPs locally, or install the hosted versions from the Claude and ChatGPT directories.
Replace the bracketed details, run the prompt, and check the returned sources and dates.
THE PROMPT LIBRARY
Browse by task or source. Open a prompt, check its required MCPs, then copy it and replace the bracketed details. Hosted SAM.gov covers opportunities, public registration and certification codes, and exclusions. Entity records are monthly snapshots; confirm current registration on SAM.gov. Opted-out entities are not included in the hosted public mirror. Local full is needed for live API details, certification dates, reps and certs, and integrity records. Check each prompt's edition note.
56 prompts
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Hosted SAM.gov supplies dated public registration, certification codes with any listed exit dates, and exclusions; use Local full for live API details and certification entry dates. Install and connect both MCPs in your AI client before running this prompt. Select a source above for setup.
Size up [COMPANY]: use USAspending to show contract obligations over the last 24 months, top agencies, and main work. Confirm the company's name and UEI. With SAM.gov, add registration status, returned certification evidence, and exclusions. If Hosted SAM.gov is connected, report its source file dates, distinguish certification codes from detailed certification dates, and confirm current registration on SAM.gov; flag missing evidence. Finish with two sentences on strengths and exposure.
Hosted SAM.gov supplies monthly public certification codes and any listed 8(a) exit dates, and flags exit dates that have passed; confirm current certification with SBA. Install and connect both MCPs in your AI client before running this prompt. Select a source above for setup.
Find firms with 8(a) set-aside awards under NAICS [NAICS] in USAspending. Check each selected recipient's SBA certification dates in SAM.gov and the end dates of its relevant awards. Flag documented program exit dates within 18 months that overlap with contract end dates within 12 months. Show the dates and source records. Treat missing certification data as unresolved, not proof of graduation; treat an approaching award end as a research lead, not a confirmed recompete. If SBA exit dates aren't available from the connected SAM.gov server, list the award-end leads and mark the 8(a) exit date as a check to do on SAM.gov.
Hosted SAM.gov supplies dated public registration and exclusion checks; confirm current registration on SAM.gov. Install and connect both MCPs in your AI client before running this prompt. Select a source above for setup.
Vet [COMPANY] as a teammate: check exclusions and registration expiration with SAM.gov, then use USAspending to show whether they have primed work for [AGENCY], including purchases funded there but awarded elsewhere. List other recent federal work. If Hosted SAM.gov is connected, report its source file dates and confirm current registration on SAM.gov. Flag missing evidence; opted-out entities are not included in the hosted public mirror.
Install and connect both MCPs in your AI client before running this prompt. Select a source above for setup.
Build an opportunity evidence screen for [NOTICE ID]. Pull the opportunity from SAM.gov, then use USAspending to find comparable work at that agency under the same NAICS, including award sizes, end dates, and evidence of a current incumbent. Keep public facts separate from assumptions. List the internal capability, vehicle, past performance, staffing, pricing, and risk-tolerance facts we still need; do not make the company's bid/no-bid decision from public data alone.
Install and connect both MCPs in your AI client before running this prompt. Select a source above for setup.
Find comparable federal contracts for [REQUIREMENT] under NAICS [NAICS] in USAspending, skipping ones with a different scope. For each, show how it was competed, obligations, current value, potential value with all options, and outlays (money actually paid out) where reported, naming the field behind each number, plus performance dates. Then show CALC+ ceiling rates for the matching labor categories separately. Don't turn a total award amount into an hourly rate without a documented staffing and period of performance basis.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Using the SAM.gov tool, show me federal IT work that's coming but not out for bid yet: - NAICS starting with 5415 (all computer and IT services) - Only Sources Sought and Presolicitation notices - Still open for responses First, count them by agency so I can see who's planning the most IT buying. Then list the most interesting ones in a table with response due date, title, agency, set-aside (if any), and sam.gov link. Pick the 5 biggest or most strategic opportunities and say in one line each why a company should respond now. Keep notices with no stated deadline; flag sole-source intent, and only call an opportunity big when its notice states a value.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find current SAM.gov Solicitation and Combined Synopsis/Solicitation notices for NAICS [NAICS] due between today and [N] days from now. Fetch all matches, remove duplicate notice IDs, and sort by deadline. Show title, agency, deadline and time zone, set-aside, and SAM.gov link. Exclude expired deadlines. Note snapshot date, active-file coverage, missing fields, and attachment limits.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find sources sought notices under NAICS [NAICS] from the last 60 days, then separately search notice titles for RFI. Identify the returned notice types and flag response deadlines within two weeks. If I supply PSC [PSC], run a separate PSC search, merge the results, and deduplicate by notice ID. Identify limits or missing pages instead of treating a partial search as complete.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Retrieve opportunity [NOTICE ID] from SAM.gov, including the full description when available. Summarize the requirement, response deadline, evaluation approach if stated, and any explicit incumbent references. Cite the notice and distinguish stated requirements from your interpretation. Identify attachments or amendments the MCP did not retrieve.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find contract award notices under NAICS [NAICS] posted to SAM.gov in the last [N] days. Show the winner, reported amount, award date, posting date, notice ID, and source link where available. Keep missing amounts or dates marked as missing. If few results appear, report the search coverage and offer a wider window; do not infer that no awards occurred or assume every award posts immediately.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find current SAM.gov notices for NAICS [NAICS] posted in the last 90 days by [AGENCY]. Show title, agency path, notice type, posting date, response deadline, and SAM.gov link, including postings with past deadlines. List the department, sub-tier, and office names matched by the agency filter; command names may miss subordinate field offices.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Search USAspending recipients for [COMPANY] and list every match with its lifetime award total and whether it is the parent rollup or a subsidiary record. The same company appears several times and the totals differ by a lot, so name the record you pick and use it in everything that follows. If the search returns only near-misses, try the other recipient search tool before deciding the company is not in the data.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Pull [COMPANY]'s federal contract activity over the last 12 months. For each award, show award ID, agency, NAICS, performance end date, obligations added minus removals during that window, and cumulative award obligations separately. Sort by obligations added minus removals in the window, largest first. Add "in NAICS [NAICS] only" if I want one code.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Retrieve [COMPANY]'s federal contract awards for the last two years from USAspending using the selected recipient record. Summarize obligations by awarding agency, with agency share and the underlying award count. Use compatible source filters and paginate as needed. If only a sample is retrieved, state its size and selection method and label the shares as sample shares, not the company's complete revenue concentration.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find who [COMPANY] reports subcontracting work to. Confirm its recipient identity, retrieve its ten largest contract prime awards by cumulative obligations, and search all reported subaward pages for each. List prime ID, subcontract recipient, report amount and action date. Explain that these are the company's subcontractors, not primes it works under, and that absent reports do not establish self-performance.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find [AGENCY]'s contract awards under NAICS [NAICS] above $[FLOOR] with recorded performance end dates in the next nine months. Use USAspending's available filters and paginate through the results; if end dates require local filtering, explain the coverage. Flag implausible dates, possible follow-on awards, and option-period uncertainty. Present the results as potential recompete leads, not confirmed future solicitations.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
List [COMPANY]'s USAspending contract awards with recorded performance end dates between today and [N] months from now. Sort the selected results by end date and report the recipient identity, award ID, agency, amount field, and end date. If the tool cannot filter directly by end date, paginate and filter the retrieved records. State incomplete coverage and distinguish award end dates from confirmed recompete plans.
Hosted SAM.gov supplies dated public exclusion records; verify current findings on SAM.gov. Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Check whether [COMPANY / UEI] has any exclusion records. If records exist, tell me whether any are currently active and what they are for. If Hosted SAM.gov is connected, report the source file name and date. Entity records are monthly snapshots; opted-out entities are not included in the hosted public mirror. Confirm current registration and material exclusion findings on SAM.gov before relying on them.
Hosted SAM.gov supplies monthly public registration records and certification codes; confirm current registration on SAM.gov. Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Look up [COMPANY] in SAM.gov and tell me: is the registration active, when does it expire, what is its primary NAICS, and what socioeconomic categories does it hold? If more than 1 active registration exists, say how many and name the UEI you picked before answering. Do not infer corporate ownership from a shared address alone. If Hosted SAM.gov is connected, report the source file name and date. Entity records are monthly snapshots; opted-out entities are not included in the hosted public mirror. Confirm current registration and material exclusion findings on SAM.gov before relying on them.
Hosted SAM.gov shows certification codes and any listed exit dates; entry dates and live status need the Local full SAM.gov edition. Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Retrieve [COMPANY]'s SBA certification fields from its SAM.gov entity record. Report each listed program, status, entry date, and exit date using the source's own labels. Distinguish a documented date from an inferred current status. An empty certification list or a historical set-aside award does not by itself prove present eligibility, graduation, or ineligibility.
This prompt needs the Local full SAM.gov edition for live API or detailed certification/integrity fields. Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
For [UEI], retrieve the current SAM.gov registration status and exclusions, then request the separately available entity integrity information. Report the source, retrieval date, entity match, and any access restrictions or missing records. Present the evidence and unresolved gaps without making a responsibility determination.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Using the confirmed recipient UEI for [COMPANY], retrieve USAspending dated contract transactions for [START FY] through [END FY], one fiscal year at a time. Report query coverage, transaction and distinct-award counts, and the earliest returned action date. Page within a stated scope. Distinguish reporting gaps, unsupported periods and empty responses; the earliest returned action is not proof of the company's first federal award.
Hosted SAM.gov supplies monthly public registration records, certification codes, and any listed exit dates; entry dates and live details require Local full. Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Build a teaming shortlist from active SAM.gov registrants in [STATE] with NAICS [NAICS] anywhere on their records and [SOCIOECONOMIC STATUS]. Use the server's appropriate business-type or SBA-certification filter. Report the total count and returned page size, paginate within the agreed scope, and deduplicate by UEI. Show each firm's name, UEI, relevant NAICS, registration expiration, and returned certification status and dates. Flag missing evidence and explain search coverage. If Hosted SAM.gov is connected, report the source file name and date. Entity records are monthly snapshots; opted-out entities are not included in the hosted public mirror. Confirm current registration and material exclusion findings on SAM.gov before relying on them.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Show [AGENCY]'s USAspending contract obligations under NAICS [NAICS] for the most recently completed fiscal year. State the exact fiscal-year dates, show the available sub-agency breakdown, and list the top ten recipients. Distinguish a single returned category from complete organizational detail and identify any source or filter limitations.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Show federal contract obligations under NAICS [NAICS] by place-of-performance state for the most recently completed fiscal year. State the exact period and geography basis, sort the states by amount, and separate unknown locations. Do not describe recipient headquarters spending as the location where work is performed.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Estimate the share of [AGENCY]'s contract obligations under NAICS [NAICS] associated with small-business set-aside codes over the last two years. Use matching periods and award filters for numerator and denominator, list the codes included, and show the calculation. Keep unknown classifications separate where the source allows. Explain that set-aside coding is not the same measure as all awards to small businesses.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Show [AGENCY]'s USAspending contract obligations under NAICS [NAICS] for the last five completed fiscal years. Give the exact fiscal years, amounts, year-over-year changes, and a short explanation of the trend. Keep any current partial fiscal year separate. Treat past obligations as market context rather than a forecast of future opportunities.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Identify large IDVs under NAICS [NAICS] in USAspending, stating the amount field and period used for ranking. For the vehicle I select, retrieve its detail and linked child awards. Use additional searches only when their relationship to the vehicle can be supported. Report missing links or incomplete coverage; do not conclude that an active vehicle has no orders solely from an empty response.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
What NAICS code covers [BUSINESS ACTIVITY]? Give me the code and the closest alternates so I do not file under the wrong one.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Use the eCFR MCP to retrieve the currently available size-standard table in 13 CFR 121.201 for NAICS [CODE]. Return the matching industry, dollar or employee threshold, and relevant exceptions or footnotes, with the source date and citation. If the table, row, or notes cannot be retrieved completely, state that limitation and do not supply a threshold from memory.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find PSC codes for [SERVICE AND DELIVERY MODEL], with official names. Check current or retired status in the official PSC manual; mark unverified status unknown. Separate codes for current opportunities from legacy codes for award history.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Use the available PSC reference tools to retrieve PSC [CODE], its official description, and related categories. Report active or retired status only if the returned reference explicitly provides it. If status or a detailed definition is unavailable, identify that gap instead of inferring it from a missing search result.
Install and connect both MCPs in your AI client before running this prompt. Select a source above for setup.
Find the PSC code for [SERVICE], then search SAM.gov opportunities under that exact code with a response deadline still open. Codes first, opportunities second, one chain.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
I do not know GSA's exact labor category title for [ROLE]. Show me the closest matching titles with how many rate records each carries, so I search the right string.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Show CALC+ ceiling-rate distributions for labor-category titles matching [LABOR CATEGORY]. Identify the exact titles, filters, record count, and available percentile or summary statistics. Compare relevant education and experience groups using supported filters. Explain whether results combine multiple titles, and do not present calculated precision beyond what the source supports.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Pull [COMPANY]'s GSA rate card and every row whose labor category contains [KEYWORD]. Ask for the total category count and page through until you have every row; the card reports which rows came back and whether more remain. There is no server-side vendor-plus-keyword search, so the keyword screen happens on the rows you fetched.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Position $[RATE]/hr for [LABOR CATEGORY] against relevant awarded CALC+ ceiling-rate distributions. Show the comparison set, percentile band, geography, education and experience differences, and data limitations. Do not call the rate defensible, reasonable, fair, or acceptable; leave that determination to the authorized official.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Use BLS OEWS to find median and 75th-percentile annual wages for [OCCUPATION] in [METRO AREA]. Confirm the available data year, SOC code, and geographic match first. Report missing, suppressed, or unavailable figures explicitly, along with the source period; do not silently substitute a different year or location.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Compare wages for [OCCUPATION] across [METRO 1] and [METRO 2], then pull the national median separately as the baseline. I am deciding where a position can realistically be staffed.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Give me the raw BLS wage for [OCCUPATION] in [METRO], median and 10th and 90th percentile, current data year, with no loaded-rate estimate attached. The burden math is mine.
Install and connect both MCPs in your AI client before running this prompt. Select a source above for setup.
Compare the BLS OEWS wage for [OCCUPATION] in [METRO] with CALC+ ceiling rates for a closely matched labor category. Keep raw wages and fully burdened ceiling rates distinct. If showing a burdened-wage scenario, use [BURDEN MULTIPLIER] or ask me to supply it, and show the formula. Explain occupation, experience, geography, and pricing-basis differences.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Compare median wages for [OCCUPATION 1], [OCCUPATION 2], and [OCCUPATION 3] side by side in [METRO]. I am pricing a mixed labor category task order and want the whole staffing picture in one table, not separate lookups.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Retrieve GSA lodging and M&IE rates for [CITY, STATE] in [FISCAL YEAR]. Show seasonal lodging changes, the matched locality, and the rate period. Identify an unmatched or fallback locality clearly before using the rates in an estimate.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Estimate per-traveler lodging and M&IE for [N] nights in [CITY, STATE] during [MONTH, YEAR]. Use the matching fiscal-year rates, identify the locality, show the daily components, and apply the tool's first/last-day M&IE treatment explicitly. State the assumed travel days and exclude airfare and other expenses unless separately supplied. Ask for a date if it is missing instead of silently pricing another season.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Look up GSA per diem for ZIP [ZIP] in [FISCAL YEAR]. Report the locality actually returned, lodging seasonality, and M&IE. If the ZIP lookup also falls back or fails to match, keep that uncertainty visible rather than treating the location as confirmed.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Retrieve FAR [CITATION] using the eCFR MCP's latest available Title 48 date. Quote the relevant text and provide the citation and source date. Inspect its version history and compare relevant revisions before calling a change substantive; distinguish publication, amendment, effective, and retrieval dates when the source supplies them.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find sections in FAR Part [PART] with eCFR version changes in the last year, then compare before and after section by section for the changes relevant to [TOPIC]. State the dates used and distinguish substantive wording changes from editorial or structural changes. Identify incomplete comparisons rather than claiming the entire part was reviewed.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find the FAR definition of [TERM] using the eCFR MCP. Retrieve the relevant section or complete matching definition, including numbered subparagraphs and exceptions. Give the citation and source date. If a large section such as FAR 2.101 is truncated, identify the missing portion and do not present a partial definition as complete.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Search Federal Register documents on [TOPIC] from the last 6 months across all document types, ordered by relevance; the live items are often notices and RFIs, not just proposed rules. For anything with an open comment period, give me the deadline.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Count Federal Register documents on [TOPIC] by agency for the last twelve months using the available facet tools. State the date range, search terms, document types, and returned counts. Use the result to choose which agencies to examine next; a count alone does not indicate the significance of a policy change.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Trace FAR Case [NUMBER] through Federal Register documents in date order. Separate documents directly addressing the case from Unified Agenda entries or other notices that merely mention it. Show proposed, final, withdrawn, and effective-date information only where supported, with source links and any gaps in the retrieved history.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
What is open for comment right now on [TOPIC]? Use the Federal Register's open comment periods with a term filter for this one; the Regulations.gov version filters by agency only. Give me the docket ID, or the document number when a notice carries no docket, and the closing date.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Find FAR and DFARS proposed rules with open comment periods using the Regulations.gov MCP's available agency and document filters. Check the relevant FAR and DARS agency codes, then distinguish actual proposed rule changes from routine information-collection notices. Return the docket or document ID, title, closing date, source link, and any filter or coverage limitations.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
For docket [DOCKET ID], find organizational comments using terms such as association, chamber, coalition, or institute. Group them by the document commented on. Read full comment text or attachments before summarizing positions, and cite each source. If attachments are unreadable, say so rather than infer positions from snippets. Explain the keyword selection; it is not all comments or a measure of consensus.
Install and connect this MCP in your AI client before running this prompt. Select a source above for setup.
Use the Acquisition.gov MCP to retrieve the FAR Overhaul model text for FAR Part [PART] and find posted deviations for [AGENCY] and that part. Retrieve the relevant indexed deviation documents. Report source links, retrieval dates, and any stated effective dates or applicability language, with PDF page references. Keep the model text separate from the agency's documented action, and clearly identify missing or conflicting evidence. Do not decide which rule governs my procurement.
Install and connect both MCPs in your AI client before running this prompt. Select a source above for setup.
Compare the current codified text for FAR [CITATION] using eCFR with the relevant FAR Overhaul model part and [AGENCY]'s posted deviation using Acquisition.gov. Show the three sources separately, cite exact sections or PDF pages, and explain the differences. Include retrieval dates and document-stated dates. Do not treat model text as agency adoption or infer applicability from a filename.
MADE FOR READING AND SHARING
The full library in a clean, white-and-green PDF. 56 prompts for nine MCP sources, organized by the work you want to do.
Download the PDFOctober 2026 · PDF · 16 pages
CONNECT YOUR SOURCES
Set each one up locally from its setup guide, or install the hosted version from the Claude and ChatGPT directories. Every card shows the server's tool count.
Contract opportunities, entity registrations, SBA certifications, and exclusions.
20 tools. Everything in hosted, plus contract awards, subawards, reps and certs, and past terminations and legal proceedings.
Contracts, grants, loans, recipients, agencies, and subawards.
Awarded labor-category ceiling rates and comparison data.
Occupational wages by geography and data year from the Bureau of Labor Statistics.
Lodging and meals-and-incidental-expense rates by locality.
Codified regulatory text, dates, and version comparisons.
Published rules, notices, comment periods, and FAR cases.
Rulemaking dockets, documents, and public comments.
FAR Overhaul model text, posted agency deviations, and guidance.
Use a compatible MCP client and confirm the server's tools are available before running a prompt. Some sources require a free API key. Current setup and testing details live with each server.