Server data from the Official MCP Registry
Federal Audit Clearinghouse (FAC) MCP — US single-audit data.
Federal Audit Clearinghouse (FAC) MCP — US single-audit data.
Remote endpoints: streamable-http: https://gateway.pipeworx.io/fac/mcp
Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. Trust signals: trusted author (1267/1280 approved). 1 finding(s) downgraded by scanner intelligence.
36 tools verified · Open access · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-pipeworx-io-fac": {
"url": "https://gateway.pipeworx.io/fac/mcp"
}
}
}From the project's GitHub README.
Federal Audit Clearinghouse MCP — US single-audit filings (Uniform Guidance, formerly OMB A-133): who spends federal grant money, under which Assistance Listing program, and what the auditors found. api.data.gov key.
fac_search_audits(auditee_name|uei|ein|state|audit_year|min_total_expended, ...) — find audits; returns report_id, organization identity, total federal awards expended, oversight agency, FAC acceptance date.fac_get_audit(report_id, ...) — one audit plus every federal program row on its Schedule of Expenditures of Federal Awards (Assistance Listing number, program name, dollars expended, major-program flag, opinion type), auditee/auditor contact detail, and findings when FAC carries them.fac_audit_findings(report_id | auditee_name | uei, ...) — findings recorded against an audit, or swept across every audit one recipient filed, rolled up into a severity summary (material weaknesses, significant deficiencies, questioned costs, repeat findings, modified opinions). include_text attaches the narrative finding text.fac_federal_awards_by_program(cfda | federal_agency_prefix + federal_award_extension, ...) — who expended money under a CFDA number (e.g. 93.224), ranked by dollars, joined to recipient name/state/year.fac_recipient_audit_history(uei | auditee_name | ein, ...) — one recipient's audits year by year with total expended per year and a percent-change read on the trend.Forgiving aliases throughout: query / q / name for auditee_name; cfda / program_number / assistance_listing / program all accept "93.224", "93-224", "93224", or a bare "93" for every program at that agency.
Platform key (PLATFORM_DATAGOV_KEY) with BYO fallback via ?_apiKey=<key>.
This is an api.data.gov umbrella key — the same key works across every federal API behind the umbrella. Register free at https://api.data.gov/signup. Sent as the X-Api-Key header. A registered key gets 1,000 requests/hour; DEMO_KEY works for smoke tests but caps around 30/hour and 50/day per source IP.
https://api.fac.gov/general — one row per accepted audit submission (auditee identity, audit year, total federal awards expended, oversight agency, acceptance date)https://api.fac.gov/federal_awards — one row per federal program inside an audit (agency prefix + award extension, program name, amount expended, major-program flag, report type)https://api.fac.gov/findings — audit findings per report; carries auditee_uei and audit_year alongside report_id, plus the is_material_weakness / is_repeat_finding / is_questioned_costs Y-N flags and type_requirementhttps://api.fac.gov/findings_text — narrative finding text, keyed report_id + finding_ref_number (attached only when include_text: true)Gotchas. The umbrella lies about status codes: api.data.gov reports throttling as a body carrying OVER_RATE_LIMIT that arrives with HTTP 200 as often as HTTP 429, so every response body is inspected before it is treated as data — a status-only check silently hands an error object back to the caller as if it were rows. That body is usually JSON ({"error":{"code":"OVER_RATE_LIMIT",...}}) but the umbrella also serves an HTML error page with the same code, so the raw text is scanned for the known umbrella codes too; without that, an HTML 200 reads as a malformed response instead of the plain "you are throttled" it actually is. Relatedly, a 2xx whose body is not a JSON array is treated as an upstream failure, never as an empty table — returning "no rows" for a broken response is the worst possible answer to a diligence question, and it is exactly what a naive Array.isArray(body) ? body : [] does. api.fac.gov also emits HTTP 408 ("Oops... Request Timeout") under load rather than queueing, which is called out as a retry rather than a client error. It is a PostgREST API, so filters are operator-prefixed (?auditee_name=ilike.*stanford*, ?audit_year=eq.2023, ?total_amount_expended=gte.1000000) and an unknown column produces a 400, not an ignored parameter; that is why the supplementary lookups (/findings, /findings_text — both verified live) degrade to an available: false note rather than throwing: a renamed table must not take the primary answer down with it. federal_agency_prefix and federal_award_extension are stored separately and only mean something concatenated: prefix 93 + extension 224 is Assistance Listing 93.224, so callers who pass the dotted number get it split for them and every response echoes assistance_listing back. The extension is stored zero-padded to three characters (47.076, never 47.76), so a numeric extension is padded before it is sent — an unpadded one matches nothing rather than erroring. Every numeric-looking column is text: audit_year comes back as "2023", and the Y/N flags are single-character strings, so values are coerced on the way out and eq. filters are written against the text form. /federal_awards carries no auditee columns — recipient name, state and audit year live on /general, so fac_federal_awards_by_program joins the two by report_id; when a state or audit_year filter is set it over-fetches the top rows by dollar amount and filters after the join, and reports rows_scanned so a caller can tell a deeper scan is needed. Finally, zero findings is an answer, not a gap: a clean single audit legitimately has no rows in /findings, which is returned as found: false, reason: 'no_findings' with the audits that were checked, distinct from reason: 'findings_table_unavailable'. Entities spending under the ~$750k/yr federal threshold never file at all, so an absent organization is usually below threshold rather than missing.
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"fac": {
"url": "https://gateway.pipeworx.io/fac/mcp"
}
}
}
Or connect to the full Pipeworx gateway for access to all 1375+ data sources:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}
Instead of calling tools directly, you can ask questions in plain English:
ask_pipeworx({ question: "your question about Fac data" })
The gateway picks the right tool and fills the arguments automatically.
MIT
Be the first to review this server!
by Modelcontextprotocol · Developer Tools
Read, search, and manipulate Git repositories programmatically
by Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.
by mcp-marketplace · Developer Tools
Create, build, and publish Python MCP servers to PyPI — conversationally.