Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
One MCP for devs incl Brave,Google,Tavily,Context7,AWS,Excalidraw,DB,GitHub,DevTools,Playwright
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Der Entwickler hat in der Registry keine Installationsangaben gemacht. Sieh dir unten die README des Entwicklers an.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto beycom bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (2.2.2) kam vor 7 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
🧿 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
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