Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
One MCP for devs incl Brave,Google,Tavily,Context7,AWS,Excalidraw,DB,GitHub,DevTools,Playwright
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
El creador no incluyó detalles de instalación en el registro. Consulta el README del creador más abajo.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub beycom, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (2.2.2) llegó al registro hace 7 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
🧿 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
Solo se muestra el principio; lee el resto en el repo