Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
One MCP for devs incl Brave,Google,Tavily,Context7,AWS,Excalidraw,DB,GitHub,DevTools,Playwright
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
作者はレジストリにインストール情報を載せていません。下にある作者のREADMEをご覧ください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント beycom で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(2.2.2)がレジストリに届いたのは7 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
🧿 One MCP for developers - no tool tax, no context rot. 250+ tools your agent calls as Python code: search, docs, files, databases, diagrams, vision, memory - plus a proxy for every MCP server you already use.
Works with Claude Code, Cursor, Codex - any MCP client
Every MCP server re-sends its tool definitions on every request: 3K-30K tokens each. Connect 5 servers and you've burned 55K tokens before the conversation starts. Connect 10+ and you're at 100K.
The math is brutal: Claude Opus 4.5 at $5/M input tokens, 20 days × 10 conversations × 10 messages × 3K tokens = $30/month per MCP server - even if you never use the tools.
And then there's context rot - your AI literally gets dumber as you add more tools (Chroma Research, 2025).
OneTool is one MCP server that exposes tools as a Python API. Instead of reading tool definitions, your agent writes code:
__onetool brave.search(query="react 19 server components")
Configure one MCP server. Use unlimited tools - ~2K tokens no matter how many you add.
"Agents scale better by writing code to call tools instead. This reduces the token usage from 150,000 tokens to 2,000 tokens...a cost saving of 98.7%"
97% fewer tokens. 30× lower cost. No context rot. (Measured - 47,660 → 1,131 input tokens against 18 MCP servers.)
Because tools are Python functions, your agent does things tool-call JSON can't: batch, chain, loop, compose.
__onetool
page = webfetch.fetch(url="https://fastmcp.dev/changelog", output_format="markdown") notes = ot_llm.transform(data=page, prompt="Summarise the breaking changes") mem.write(topic="deps/fastmcp", content=notes)
Three packs, one request. Intermediate results flow between tools as variables - the page body never touches your context window, and the summarising runs on a cheap model instead of your expensive coding agent.
Every call is explicit and reviewable - __onetool brave.search(query="...") shows you exactly what runs. No tool-selection guessing.
And the runtime is built for how agents actually type:
mem.search(q="auth") works - any unambiguous parameter prefix resolves (q= → query=)wb.draw(...) works - packs have short aliases (wb, ctx, img)github.listRepositories() works on proxied servers - snake/camel/Pascal all resolveBootstrap (installs uv if missing, installs OneTool, initialises config, prints MCP config):
curl -LsSf https://onetool.beycom.online/install.sh | sh # macOS / Linux
irm https://onetool.beycom.online/install.ps1 | iex # Windows (PowerShell)
Or install manually with uv:
uv tool install 'onetool-mcp[all]' # everything
onetool init --config ~/.onetool
Then print ready-to-paste MCP client config with resolved absolute paths and add it to your client (claude-code, claude-desktop, cursor, or vscode):
onetool init mcp-config --client claude-code # or omit --client for all four
That's it. All 250+ tools work out of the box.
Verify: onetool init validate --config ~/.onetool/onetool.yaml
Install the ot-ref skill into your agent with vercel-labs/skills - it teaches the call conventions and ships a greppable index of every tool signature:
npx skills add https://github.com/beycom/onetool-mcp --skill ot-ref --agent claude
| Search & docs | Brave, Google-grounded, and Tavily search (each with batch + answer modes), Context7 library docs, web fetch with extraction controls |
| Files & data | File ops with path boundaries, full Excel control, SQL databases, PDF/Word/PowerPoint → Markdown, ripgrep, package versions |
| Context economy | ctx handles for large outputs, partial file reads (toc/slice), image vision on a dedicated cheap model (zero host tokens), LLM delegation (10× savings) |
| Persistent state | mem memory with semantic + keyword search, history and rollback; knowledge RAG bases with AI enrichment; localhist Git-backed project snapshots |
| Visual | Live Excalidraw whiteboard with a Mermaid-compatible DSL and offline auto-layout, Mermaid/PlantUML/D2 diagrams, architecture models → draw.io-editable SVG |
| Runtime | MCP server proxy with runtime enable/disable/restart, direct CLI/API into the running process, ot-ref agent skill, in-conversation tool forging |
| Trust | age-encrypted secrets backed by your OS keychain, AST validation, path boundaries, output sanitisation, runtime stats with estimated savings |
28 packs, 253 tools ready to use (console in beta):
| Pack | Tools | Extra | Description |
|---|---|---|---|
arch | generate, validate, bundle_solution, … | [dev] | Architecture models → draw.io-editable SVG |
brave | search, news, image, video, search_batch | [util] | Brave web search |
chrome_util | highlight_element, guide_user, … | [dev] | Browser annotations (Chrome DevTools) |
console *(beta)* | show, display, list, read, clear | Messages to the upcoming onetool-console app | |
context7 | search, doc | [dev] | Library documentation |
convert | pdf, word, powerpoint, excel, auto | [util] | Documents → Markdown |
db | query, schema, tables, sample | [dev] | SQL databases |
diagram | render_diagram, batch_render, get_template, … | [dev] | Mermaid / PlantUML / D2 via Kroki |
excel | read, write, formula, create_table, … (24 tools) | [util] | Full Excel control |
file | read, write, edit, grep, slice, toc, … (16 tools) | [util] | File ops with path boundaries |
ground | search, dev, docs, reddit, search_batch | [util] | Google-grounded search with sources |
knowledge | search, ask, write, related, … (15 tools) | [util] | RAG knowledge bases (hybrid search) |
localhist | save, diff, restore, autosave_start, … (15 tools) | [dev] | Git-backed local history snapshots |
mem | write, search, ask, history, rollback, … (31 tools) | [util] | Persistent memory with semantic search |
ot | help, tools, stats, status, result, … (18 tools) | Introspection and management | |
ot_context (ctx) | write, read, grep, slice, toc, ask, … (13 tools) | Smart context store for large outputs | |
ot_forge | create_ext, validate_ext | Scaffold new tool packs | |
ot_image (img) | load, ask, clip_ask, summary, … (9 tools) | Image vision via a dedicated model | |
ot_llm | transform, transform_file | LLM-powered transforms | |
ot_secrets | set, encrypt, audit, rotate, … (8 tools) | Encrypted secrets management | |
ot_servers | enable, disable, restart, status | Runtime control of proxied servers | |
ot_timer | start, stop, elapsed, list, clear | Named timers | |
package | pypi, npm, version, audit, models | [dev] | Package versions and staleness |
play_util | highlight_element, guide_user, … | [dev] | Browser annotations (Playwright) |
ripgrep | search, count, files, types | [dev] | Fast code search |
tavily | search, research, extract, search_batch, … | [util] | AI-native search and extraction |
webfetch | fetch, fetch_batch | [dev] | Web content extraction |
whiteboard (wb) | open, draw, layout, screenshot, … (22 tools) | [util] | Live Excalidraw canvas |
📖 Complete tools reference — every signature, generated from source
Keep the MCP servers you already use. Wrap them in YAML and call them explicitly - as Python namespaces, without their tool tax:
# .onetool/onetool.yaml
servers: local_tools: type: stdio command: npx args: ["-y", "some-mcp-server@latest"] private_api: type: http url: ${PRIVATE_MCP_URL} auth: type: bearer token: ${PRIVATE_MCP_TOKEN}
__onetool private_api.read_resource(path="README.md")
Proxied servers can be enabled, disabled, and restarted mid-conversation with ot_servers - no client restart.
onetool init walks you through encrypted secrets: values in secrets.yaml are age-encrypted, the private key lives in your OS keychain, and decryption happens transparently at load.
# secrets.yaml - safe to inspect, safe to commit
brave_api_key: age1enc:YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNT...
Works as an MCP server and as a direct CLI bridge into the same running process - loaded config, secrets, and proxy connections stay warm. Useful for agent harnesses, scripts, and automation:
# Recommended local MCP root mode: stdio
onetool serve --config .onetool/onetool.yaml
onetool serve --transport http --config .onetool/onetool.yaml --host 127.0.0.1 --port 8767 --path /mcp
onetool
冒頭だけを表示しています。続きはリポジトリで読めます