Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Search companies, enrich contacts, and reveal emails and phones from your AI agent.
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.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Funciona en Claude para web, escritorio y móvil:
https://mcp.fiber.ai/mcp/v2/Ejecuta esto en tu terminal
claude mcp add --transport http fiber https://mcp.fiber.ai/mcp/v2/Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"fiber": {
"url": "https://mcp.fiber.ai/mcp/v2/"
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"fiber": {
"type": "http",
"url": "https://mcp.fiber.ai/mcp/v2/"
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
ChatGPT solo se conecta a servidores en internet:
https://mcp.fiber.ai/mcp/v2/Los nombres de los menús pueden variar un poco según el plan y con el tiempo.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Todavía no hemos leído la lista de herramientas de este servidor; revisamos los endpoints por turnos.
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 el dominio fiber.ai (el registro comprueba quién es dueño del dominio)
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Aún sin revisar; revisamos los endpoints por turnos
Aún sin revisar; revisamos los endpoints por turnos
Aún sin revisar; leemos la lista de herramientas cuando revisamos el endpoint
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 la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.
El repo de GitHub cambió por última vez –, y la última versión (1.0.0) llegó al registro hace 8 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.
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.
The Model Context Protocol (MCP) server provides a standardized interface that allows any compatible AI agent to access Fiber AI's data and tools — search companies, enrich contacts, reveal emails, and more — directly from your editor.
If you are a coding agent and need to pick between MCP and the REST API, start with the canonical agent-facing docs on the API:
https://api.fiber.ai/ai-docs/ .mdRule of thumb: use MCP when you're acting inside an IDE / chat and each operation is a tool call; use the REST API (via @fiberai/sdk or fiberai) when you're building an autonomous script or a production pipeline.
Fiber AI offers three remote MCP servers:
| Server | URL | Auth | Best For |
|---|---|---|---|
| V2 | https://mcp.fiber.ai/mcp/v2 | API key | Auto-generated direct tools for the top ~10 priority operations (companySearch_tool, peopleSearch_tool, etc.) |
| V3 | https://mcp.fiber.ai/mcp/v3 | OAuth (SSO) | Direct tools for every public operation with compact descriptions; the model can call or expand any tool on demand |
| Core | https://mcp.fiber.ai/mcp | API key | 5 meta-tools that discover and call any of 100+ API endpoints (search_endpoints, list_tag_packs, list_all_endpoints, get_endpoint_details_full, call_operation) |
Which one should I use? V2 is the fastest path for the most common flows with an API key. V3 is the most ergonomic for broad agent coverage — it exposes every public operation as a direct tool with compact descriptions, authenticated via browser-based SSO login instead of a pasted key. Core keeps the tool count tiny (5) and lets the agent discover endpoints at runtime; it uses the same API-key auth as V2. You can register more than one; the server names (
fiber-ai-v2,fiber-ai-v3,fiber-ai-core) stay distinct.
The Fiber AI plugin bundles these MCP servers with 16 skills (search, enrich, audiences, recruiting and SDR playbooks) and 7 persona subagents (ai-sdr, ai-recruiter, gtm-strategist, and more) for Claude Code, Cursor, Gemini CLI, OpenCode, Codex, and VS Code. See its install guide. This repo covers the MCP servers only.
Get an API key at fiber.ai/app/api for V2 and Core. The examples read it from a FIBER_API_KEY environment variable. V3 needs no key: your client opens a browser for SSO login on first connect.
Connect directly with the config for your client below, or through Smithery.
Fiber AI is listed on Smithery as fiberai/fiber-mcp (V2) and fiberai/fiber-core (Core). Install into your client with one command:
npx -y @smithery/cli@latest mcp add fiberai/fiber-mcp --client cursor
Replace cursor with your client: claude-code, claude, vscode, codex, gemini-cli, windsurf, opencode, cline, goose, and more (npx -y @smithery/cli@latest mcp add --help lists them all). Use fiberai/fiber-core for Core. On first connect your client opens Smithery in the browser to sign in and set your Fiber API key.
To use it as a Smithery connection instead (for agents that call tools through the Smithery CLI):
npx -y @smithery/cli@latest mcp add fiberai/fiber-mcp --id fiber-ai-v2 \
--headers "{\"x-api-key\": \"$FIBER_API_KEY\"}" npx -y @smithery/cli@latest tool list fiber-ai-v2
Paste a link into your browser address bar and press Enter (Cursor must be installed):
V2:
cursor://anysphere.cursor-deeplink/mcp/install?name=fiber-ai-v2&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vbWNwLmZpYmVyLmFpL21jcC92MiJ9
V3 (OAuth):
cursor://anysphere.cursor-deeplink/mcp/install?name=fiber-ai-v3&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vbWNwLmZpYmVyLmFpL21jcC92MyJ9
Core:
cursor://anysphere.cursor-deeplink/mcp/install?name=fiber-ai-core&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vbWNwLmZpYmVyLmFpL21jcCJ9
The links don't include your key; give it to the agent in chat, or add it to ~/.cursor/mcp.json (or .cursor/mcp.json in your project):
{
"mcpServers": { "fiber-ai-v2": { "type": "http", "url": "https://mcp.fiber.ai/mcp/v2", "headers": { "x-api-key": "${env:FIBER_API_KEY}" } }, "fiber-ai-v3": { "type": "http", "url": "https://mcp.fiber.ai/mcp/v3" }, "fiber-ai-core": { "type": "http", "url": "https://mcp.fiber.ai/mcp", "headers": { "x-api-key": "${env:FIBER_API_KEY}" } } } }
claude mcp add --transport http fiber-ai-v2 https://mcp.fiber.ai/mcp/v2 \
--header "x-api-key: $FIBER_API_KEY"
claude mcp add --transport http fiber-ai-v3 https://mcp.fiber.ai/mcp/v3
claude mcp add --transport http fiber-ai-core https://mcp.fiber.ai/mcp \ --header "x-api-key: $FIBER_API_KEY"
Run /mcp inside a Claude Code session to verify the connection and complete the V3 login.
Claude Desktop and claude.ai add remote servers as custom connectors, which authenticate with OAuth and can't send an API-key header. Use V3:
https://mcp.fiber.ai/mcp/v3 and sign in when prompted.You can also add https://mcp.fiber.ai/mcp/v2 as a connector and give the agent your key in chat (see Authentication).
Add to ~/.codex/config.toml:
[mcp_servers.fiber-ai-v2]
url = "https://mcp.fiber.ai/mcp/v2" env_http_headers = { "x-api-key" = "FIBER_API_KEY" }
[mcp_servers.fiber-ai-v3] url = "https://mcp.fiber.ai/mcp/v3"
[mcp_servers.fiber-ai-core] url = "https://mcp.fiber.ai/mcp" env_http_headers = { "x-api-key" = "FIBER_API_KEY" }
env_http_headers sends the value of the FIBER_API_KEY environment variable as the x-api-key header. Then sign in to V3:
codex mcp login fiber-ai-v3
The Codex IDE extension and the Codex app read the same ~/.codex/config.toml.
gemini mcp add -t http -H "x-api-key: $FIBER_API_KEY" fiber-ai-v2 https://mcp.fiber.ai/mcp/v2
gemini mcp add -t http fiber-ai-v3 https://mcp.fiber.ai/mcp/v3 gemini mcp add -t http -H "x-api-key: $FIBER_API_KEY" fiber-ai-core https://mcp.fiber.ai/mcp
Add -s user to install for every project instead of the current one. Run gemini mcp list to verify, and /mcp auth fiber-ai-v3 inside a session to sign in to V3.
Add to opencode.json in your project (or ~/.config/opencode/opencode.json):
{
"$schema": "https://opencode.ai/config.json", "mcp": { "fiber-ai-v2": { "type": "remote", "url": "https://mcp.fiber.ai/mcp/v2", "headers": { "x-api-key": "{env:FIBER_API_KEY}" } }, "fiber-ai-v3": { "type": "remote", "url": "https://mcp.fiber.ai/mcp/v3" }, "fiber-ai-core": { "type": "remote", "url": "https://mcp.fiber.ai/mcp", "headers": { "x-api-key": "{env:FIBER_API_KEY}" } } } }
Run opencode mcp list to verify, and opencode mcp auth fiber-ai-v3 to sign in to V3.
Add to .vscode/mcp.json in your workspace (VS Code reads servers from the top-level servers key):
{
"inputs": [ { "type": "promptString", "id": "fiber-api-key", "description": "Fiber AI API key", "password": true } ], "servers": { "fiber-ai-v2": { "type": "http", "url": "https://mcp.fiber.ai/mcp/v2", "headers": { "x-api-key": "${input:fiber-api-key}" } }, "fiber-ai-v3": { "type": "http", "url": "https://mcp.fiber.ai/mcp/v3" }, "fiber-ai-core": { "type": "http", "url": "https://mcp.fiber.ai/mcp", "headers": { "x-api-key": "${input:fiber-api-key}" } } } }
VS Code prompts for the key once and stores it securely. Start the servers from MCP: List Servers.
Open the Cascade panel's ... menu → Open MCP config file, and add:
{
"mcpServers": { "fiber-ai-v2": { "serverUrl": "https://mcp.fiber.ai/mcp/v2", "headers": { "x-api-key": "${env:FIBER_API_KEY}" } }, "fiber-ai-v3": { "serverUrl": "https://mcp.fiber.ai/mcp/v3" }, "fiber-ai-core": { "serverUrl": "https://mcp.fiber.ai/mcp", "headers": { "x-api-key": "${env:FIBER_API_KEY}" } } } }
Open Settings → AI → MCP Servers → Add Server → Add Remote Server, or add to your settings file:
{
"context_servers": { "fiber-ai-v2": { "url": "https://mcp.fiber.ai/mcp/v2", "headers": { "Authorization": "Bearer sk_live_..." } }, "fiber-ai-v3": { "url": "https://mcp.fiber.ai/mcp/v3" }, "fiber-ai-core": { "url": "https://mcp.fiber.ai/mcp", "headers": { "Authorization": "Bearer sk_live_..." } } } }
Zed starts an OAuth login for any remote server without an Authorization header, so use the Bearer form for V2 and Core.
Most MCP-compatible tools can be configured with:
https://mcp.fiber.ai/mcp/v2 (or /mcp/v3, /mcp)x-api-key: (or Authorization: Bearer ) for V2 and Core; OAuth for V3npx -y mcp-remote https://mcp.fiber.ai/mcp/v2 --header x-api-key:$FIBER_API_KEY/mcp/v2)Direct API tools — each Fiber AI endpoint is exposed as an individual tool:
| Tool | Description |
|---|---|
companySearch_tool | Search for companies by industry, location, size, funding, etc. |
peopleSearch_tool | Search for people by title, seniority, department, etc. |
profileLiveEnrich_tool | Live-fetch a LinkedIn profile |
companyLiveEnrich_tool | Live-fetch a LinkedIn company |
getOrgCredits_tool | Check your credit balance |
getRateLimits_tool | Check your organization's rate limits |
getAutoTopupSettings_tool | Get auto top-up settings |
getAllApiKeys_tool | List your API keys |
cardsAttach_tool | Attach a card to a trial account |
getQuickstartScript_tool | Get the quickstart install script |
/mcp/v3)One direct tool per public operation (100+), with compact descriptions the model can expand on demand.
/mcp)Meta tools for dynamic endpoint discovery:
| Tool | Description |
|---|---|
search_endpoints | Search for API endpoints by keyword |
list_tag_packs | List curated groups of endpoints to narrow the catalog |
list_all_endpoints | List all available API endpoints |
get_endpoint_details_full | Get full schema details for an endpoint |
call_operation | Call any API endpoint by its operation ID |
V2 and Core require a Fiber AI API key. V3 uses OAuth (Clerk SSO) - the client opens a browser window for login and reuses the session token, no key configuration needed. Get an API key at fiber.ai/app/api.
You can supply your key in any of these three ways - pick whichever your client makes easiest:
The agent passes the key in the request body as apiKey. Simplest path: paste your key into the agent
Solo se muestra el principio; lee el resto en el repo