fac-mcp
Enables querying and analyzing US federal grant single-audit filings, including audits, findings, and federal awards, using data from the Federal Audit Clearinghouse.
README
@pipeworx/fac
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.
Tools
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_textattaches 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.
Auth
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.
Data sources
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; carriesauditee_ueiandaudit_yearalongsidereport_id, plus theis_material_weakness/is_repeat_finding/is_questioned_costsY-N flags andtype_requirementhttps://api.fac.gov/findings_text— narrative finding text, keyedreport_id+finding_ref_number(attached only wheninclude_text: true)- API docs: https://www.fac.gov/developers/ · Assistance Listing lookup: https://sam.gov/content/assistance-listings
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.
Quick Start
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"
}
}
}
Using with ask_pipeworx
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.
More
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。