Fiber AI

Fiber AI — MCP Server

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.

For AI agents

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:

• Routing index + critical rules: https://api.fiber.ai/llms.txt
• Per-operation markdown: https://api.fiber.ai/ai-docs/<operationId>.md
• Operation index: https://api.fiber.ai/ai-docs/index.md
• MCP walkthrough for LLMs: https://docs.fiber.ai/article/using-mcp-in-llms

Rule 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.

Servers

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.

Want more than MCP? Use the Fiber AI plugin

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.

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Setup

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.

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

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Cursor

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 Code

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

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:

1. Open Settings → Connectors → Add custom connector.
2. Enter 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).

---

Codex

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 CLI

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.

---

OpenCode

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.

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Visual Studio Code

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.

---

Windsurf (Devin Desktop)

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}" }
    }
  }
}

---

Zed

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.

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Others

Most MCP-compatible tools can be configured with:

• URL: https://mcp.fiber.ai/mcp/v2 (or /mcp/v3, /mcp)
• Transport: HTTP (Streamable HTTP)
• Auth: header x-api-key: <your key> (or Authorization: Bearer <your key>) for V2 and Core; OAuth for V3
• For stdio-only clients: npx -y mcp-remote https://mcp.fiber.ai/mcp/v2 --header x-api-key:$FIBER_API_KEY

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Available Tools

V2 Server (/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

V3 Server (/mcp/v3)

One direct tool per public operation (100+), with compact descriptions the model can expand on demand.

Core Server (/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

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Authentication

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:

Option A - via chat (zero config)

The agent passes the key in the request body as apiKey. Simplest path: paste your key into the agent once and it'll keep using it.

You:    Use sk_live_... as my Fiber API key.
Agent:  [calls companySearch_tool with { "apiKey": "sk_live_...", "searchParams": {...} }]

Caveat: the key ends up in chat history. Fine for personal use, not ideal for shared sessions.

Option B - via x-api-key header (recommended for IDEs)

Configure the header once in your MCP client config; the agent never sees the key.

{
  "mcpServers": {
    "fiber-ai-v2": {
      "type": "http",
      "url": "https://mcp.fiber.ai/mcp/v2",
      "headers": { "x-api-key": "sk_live_..." }
    },
    "fiber-ai-core": {
      "type": "http",
      "url": "https://mcp.fiber.ai/mcp",
      "headers": { "x-api-key": "sk_live_..." }
    }
  }
}

Most clients accept a headers field on each MCP server and can read the key from an environment variable instead of hard-coding it. The field name and variable syntax differ per client; see the Setup section for yours.

Option C - via Authorization: Bearer header

Same shape as Option B, but using the standard bearer-token header. Useful if your MCP client only supports Authorization-style auth.

"headers": { "Authorization": "Bearer sk_live_..." }

Resolution order

When more than one is present, the server resolves in this order: body/query apiKey -> x-api-key header -> Authorization: Bearer. The first non-empty value wins.

V3 (OAuth)

V3 ignores all of the above. On first connect, the client opens https://app.fiber.ai for browser-based SSO login; the resulting session token is reused on subsequent calls. No env vars, no headers, no config to write.

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Example Usage

Once connected, ask your AI agent:

• "Search for SaaS companies in New York with 50-200 employees"
• "Find the CEO of and get their work email"
• "How many credits do I have left?"
• "Enrich this LinkedIn profile: linkedin.com/in/..."

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SDKs

For building applications programmatically (not via MCP):

• TypeScript: npm install @fiberai/sdk — GitHub
• Python: pip install fiberai — GitHub

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FAQ

Connection not working? Ensure your editor supports HTTP (Streamable HTTP) MCP transport. If it only supports stdio, use the npx mcp-remote wrapper shown under Others.

Getting authentication errors? Make sure you're supplying a valid key via one of the three supported paths (body apiKey, x-api-key header, or Authorization: Bearer). See Authentication above. Get a key at fiber.ai/app/api.

Should I put the key in chat or in headers? For personal sessions, chat is fine. For shared sessions, team-config files committed to git, or anywhere chat history might leak, configure the x-api-key header at the MCP client layer so the agent never sees the raw key.

Can I use more than one server at the same time? Yes. You can register V2, V3, and Core side by side; their names stay distinct.

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License

MIT