FedRAMP Rules MCP Server
Answers questions about the FedRAMP Consolidated Rules for 2026 using search and retrieval tools on the authoritative source text with citations.
README
FedRAMP Rules MCP Server
An MCP server that answers questions about the
FedRAMP Consolidated Rules for 2026. It bundles the official markdown corpus
from fedramp/2026-markdown and
exposes it to LLM agents through search and retrieval tools, so answers come from
the authoritative source text — with citations to file paths and rule IDs.
The content is vendored at a pinned commit (see scripts/sync_content.py), so
the server works offline, responds instantly, and gives stable, reproducible
answers. Re-run the sync script to update.
Tools
| Tool | Description |
|---|---|
fedramp_search |
BM25 full-text search across the whole corpus. Optional section prefix filter; returns ranked snippets with paths. Identical-content hits (the reference/ a/b/c/d tracks) are merged. |
fedramp_get_document |
Return the full markdown of one document by its repo-relative path. |
fedramp_list_documents |
Browse the corpus tree, optionally filtered to a section. |
fedramp_get_rule |
Retrieve a rule by ID (FRC-CSO-FCP, VDR-CSO-CVE, KSI-IAM-01, …) or a NIST control ID (AC-20, SI-4), with every location it appears. Case-insensitive. |
fedramp_get_definition |
Look up a defined term by name, alias, or FRD ID (FRD-SGC). Case-insensitive. |
There is also a fedramp://source resource exposing the source repo, pinned
commit, and sync timestamp for provenance.
Install
Requires uv and Python 3.12+. The rules corpus is bundled in the package, so no clone or extra download is needed — install straight from GitHub:
uv tool install git+https://github.com/dan-fedramp/fedramp-rules-mcp
Then run the server over stdio with:
fedramp-rules-mcp
Or run it without installing (uv fetches, builds, and runs in one step):
uvx --from git+https://github.com/dan-fedramp/fedramp-rules-mcp fedramp-rules-mcp
Pin to a specific version by appending a ref, e.g.
git+https://github.com/dan-fedramp/fedramp-rules-mcp@main.
Connecting a client
Claude Code
claude mcp add fedramp-rules -- uvx --from git+https://github.com/dan-fedramp/fedramp-rules-mcp fedramp-rules-mcp
Claude Desktop / other stdio clients
Add to the client's MCP server config (e.g. claude_desktop_config.json):
{
"mcpServers": {
"fedramp-rules": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/dan-fedramp/fedramp-rules-mcp",
"fedramp-rules-mcp"
]
}
}
}
If you installed with uv tool install, you can instead set "command": "fedramp-rules-mcp" with no args.
MCP Inspector
npx @modelcontextprotocol/inspector uvx --from git+https://github.com/dan-fedramp/fedramp-rules-mcp fedramp-rules-mcp
Development
To work on the server from a local clone:
git clone https://github.com/dan-fedramp/fedramp-rules-mcp
cd fedramp-rules-mcp
uv sync # install dependencies
uv run python -m pytest -q # run the smoke tests
uv run fedramp-rules-mcp # run the server from source
Updating the bundled rules
# vendor a specific commit or branch, then commit the result
uv run python scripts/sync_content.py --ref <commit-sha-or-branch>
How it works
scripts/sync_content.pydownloads the repo tarball and extracts every.mdfile intosrc/fedramp_rules_mcp/content/, writing_meta.jsonfor provenance.content.pyloads the corpus once, strips YAML frontmatter, and parses the two structured artifacts: the glossary indefinitions.md(FRD-*terms) and the??? abstract "<ID>"rule blocks throughout the corpus.search.pybuilds an in-memory Okapi BM25 index (no external services); the tokenizer preserves hyphenated IDs so rule-ID queries match.server.pywires the five tools with Pydantic-validated inputs and markdown/JSON output.
Notes
This is an unofficial tool built on public FedRAMP content. It is not affiliated with or endorsed by FedRAMP or the GSA. Always confirm against the official source for authoritative guidance.
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。