Search companies, enrich contacts, and reveal emails and phones from your AI agent.
Search companies, enrich contacts, and reveal emails and phones from your AI agent.
Remote endpoints: streamable-http: https://mcp.fiber.ai/mcp/v2/ streamable-http: https://mcp.fiber.ai/mcp
Remote MCP endpoint verified (97ms response). Server: fiber-api. 2 trust signals: valid MCP protocol, registry import. No security issues detected.
Endpoint verified · Open access · 1 issue found
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Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"ai-fiber-mcp": {
"url": "https://mcp.fiber.ai/mcp/v2/"
}
}
}From the project's GitHub README.
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/<operationId>.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 (api_companySearch, api_peopleSearch, 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.
Install via Smithery with a single command:
npx -y @smithery/cli install @fiber-ai/mcp --client cursor
Replace cursor with your client: claude, windsurf, vscode, zed, etc.
Or browse and install from the Smithery web UI at smithery.ai/server/@fiber-ai/mcp.
Click the link below to install automatically — paste it into your browser address bar and press Enter:
Install V2:
cursor://anysphere.cursor-deeplink/mcp/install?name=FiberAI-V2&config=eyJ1cmwiOiJodHRwczovL21jcC5maWJlci5haS9tY3AvdjIifQ==
Install Core:
cursor://anysphere.cursor-deeplink/mcp/install?name=FiberAI&config=eyJ1cmwiOiJodHRwczovL21jcC5maWJlci5haS9tY3AifQ==
Or manually: open Cursor Settings → Features → MCP → "+ Add New MCP Server" → Type: HTTP → URL: https://mcp.fiber.ai/mcp/v2
The simplest path passes your key as a header so the agent never sees it in chat:
claude mcp add --transport http fiber-ai-v2 https://mcp.fiber.ai/mcp/v2 \
--header "x-api-key: $FIBER_API_KEY"
To also add the Core server:
claude mcp add --transport http fiber-ai https://mcp.fiber.ai/mcp \
--header "x-api-key: $FIBER_API_KEY"
Or, if you prefer to give the key via chat, drop the --header flag and the agent will pass apiKey in the request body when you tell it your key.
Run /mcp inside a Claude Code session to verify the connection.
From Claude settings → Connectors, add a new MCP server with the URL https://mcp.fiber.ai/mcp/v2.
Or edit your claude_desktop_config.json:
{
"mcpServers": {
"fiber-ai-v2": {
"url": "https://mcp.fiber.ai/mcp/v2",
"transport": { "type": "http" },
"headers": { "x-api-key": "sk_live_..." }
},
"fiber-ai": {
"url": "https://mcp.fiber.ai/mcp",
"transport": { "type": "http" },
"headers": { "x-api-key": "sk_live_..." }
}
}
}
The headers field is optional - if you omit it, the agent will pass apiKey in the request body when you give it your key in chat.
codex mcp add fiber-ai --url https://mcp.fiber.ai/mcp/v2
Or add to ~/.codex/config.toml:
[mcp_servers.fiber-ai]
url = "https://mcp.fiber.ai/mcp/v2"
transport = "http"
[mcp_servers.fiber-ai.headers]
x-api-key = "sk_live_..."
The [mcp_servers.fiber-ai.headers] block is optional - drop it and give the key in chat instead.
Press Ctrl/Cmd + P, search for MCP: Add Server, select Command (stdio), and enter:
npx mcp-remote https://mcp.fiber.ai/mcp/v2
Name it FiberAI and activate it via MCP: List Servers.
Or add to .vscode/mcp.json. If your VS Code version supports HTTP MCP natively, prefer the header-based shape:
{
"mcpServers": {
"fiber-ai": {
"type": "http",
"url": "https://mcp.fiber.ai/mcp/v2",
"headers": { "x-api-key": "${env:FIBER_API_KEY}" }
}
}
}
Older VS Code releases need the stdio wrapper (mcp-remote forwards your FIBER_API_KEY env var as a header):
{
"mcpServers": {
"fiber-ai": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.fiber.ai/mcp/v2",
"--header",
"x-api-key:${FIBER_API_KEY}"
]
}
}
}
Press Ctrl/Cmd + , → Cascade → MCP servers → Add custom server:
{
"mcpServers": {
"fiber-ai": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.fiber.ai/mcp/v2",
"--header",
"x-api-key:${FIBER_API_KEY}"
]
}
}
}
Press Cmd + , and add:
{
"context_servers": {
"fiber-ai": {
"source": "custom",
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.fiber.ai/mcp/v2",
"--header",
"x-api-key:${FIBER_API_KEY}"
],
"env": { "FIBER_API_KEY": "sk_live_..." }
}
}
}
Most MCP-compatible tools can be configured with:
https://mcp.fiber.ai/mcp/v2x-api-key: <your key> (or Authorization: Bearer <your key>)npx -y mcp-remote https://mcp.fiber.ai/mcp/v2 --header x-api-key:$FIBER_API_KEY/mcp/v2/)Direct API tools — each Fiber AI endpoint is exposed as an individual tool:
| Tool | Description |
|---|---|
api_companySearch | Search for companies by industry, location, size, funding, etc. |
api_peopleSearch | Search for people by title, seniority, department, etc. |
api_individualRevealSync | Reveal work email and phone for a LinkedIn profile |
api_companyLiveFetch | Get live LinkedIn data for a company |
api_personLiveFetch | Get live LinkedIn data for a person |
api_getOrgCredits | Check your credit balance |
/mcp)Meta tools for dynamic endpoint discovery:
| Tool | Description |
|---|---|
search_endpoints | Search for API endpoints by keyword |
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 once and it'll keep using it.
You: Use sk_live_... as my Fiber API key.
Agent: [calls api_companySearch with { "apiKey": "sk_live_...", "searchParams": {...} }]
Caveat: the key ends up in chat history. Fine for personal use, not ideal for shared sessions.
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 (Claude Code, Cursor, Claude Desktop, Codex, Windsurf, VS Code) accept a headers field on each MCP server. Reference your env var instead of hard-coding:
"headers": { "x-api-key": "${env:FIBER_API_KEY}" }
Authorization: Bearer headerSame 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_..." }
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 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.
Once connected, ask your AI agent:
For building applications programmatically (not via MCP):
Connection not working?
Ensure your editor supports HTTP (Streamable HTTP) MCP transport. If it only supports stdio, use the npx mcp-remote wrapper shown in the VS Code / Windsurf / Zed instructions.
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 both servers at the same time? Yes. Many users add both V2 and Core for maximum flexibility.
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