Fiber AI
БесплатноНе проверенSearch companies, enrich contacts, and reveal emails and phones from your AI agent.
Описание
Search companies, enrich contacts, and reveal emails and phones from your AI agent.
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.
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 (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.
Setup
Smithery
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.
Cursor
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
Claude Code
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: $FIBER_API_KEY"
Or, if you prefer to give the key via chat, drop the --header flag and the agent will pass apiKey in the request body when you tell it your key.
Run /mcp inside a Claude Code session to verify the connection.
Claude Desktop
From Claude settings → Connectors, add a new MCP server with the URL https://mcp.fiber.ai/mcp/v2.
Or edit your claude_desktop_config.json:
{
"mcpServers": {
"fiber-ai-v2": {
"url": "https://mcp.fiber.ai/mcp/v2",
"transport": { "type": "http" },
"headers": { "x-api-key": "sk_live_..." }
},
"fiber-ai": {
"url": "https://mcp.fiber.ai/mcp",
"transport": { "type": "http" },
"headers": { "x-api-key": "sk_live_..." }
}
}
}
The headers field is optional - if you omit it, the agent will pass apiKey in the request body when you give it your key in chat.
Codex
codex mcp add fiber-ai --url https://mcp.fiber.ai/mcp/v2
Or add to ~/.codex/config.toml:
[mcp_servers.fiber-ai]
url = "https://mcp.fiber.ai/mcp/v2"
transport = "http"
[mcp_servers.fiber-ai.headers]
x-api-key = "sk_live_..."
The [mcp_servers.fiber-ai.headers] block is optional - drop it and give the key in chat instead.
Visual Studio Code
Press Ctrl/Cmd + P, search for MCP: Add Server, select Command (stdio), and enter:
npx mcp-remote https://mcp.fiber.ai/mcp/v2
Name it FiberAI and activate it via MCP: List Servers.
Or add to .vscode/mcp.json. If your VS Code version supports HTTP MCP natively, prefer the header-based shape:
{
"mcpServers": {
"fiber-ai": {
"type": "http",
"url": "https://mcp.fiber.ai/mcp/v2",
"headers": { "x-api-key": "${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:${FIBER_API_KEY}"
]
}
}
}
Windsurf
Press Ctrl/Cmd + , → Cascade → MCP servers → Add custom server:
{
"mcpServers": {
"fiber-ai": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.fiber.ai/mcp/v2",
"--header",
"x-api-key:${FIBER_API_KEY}"
]
}
}
}
Zed
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:${FIBER_API_KEY}"
],
"env": { "FIBER_API_KEY": "sk_live_..." }
}
}
}
Others
Most MCP-compatible tools can be configured with:
- URL:
https://mcp.fiber.ai/mcp/v2 - Transport: HTTP (Streamable HTTP)
- Auth: header
x-api-key: <your key>(orAuthorization: Bearer <your key>) - For stdio-only clients:
npx -y mcp-remote https://mcp.fiber.ai/mcp/v2 --header x-api-key:$FIBER_API_KEY
Available Tools
V2 Server (/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 |
Core Server (/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 |
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 api_companySearch 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 (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}" }
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.
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/..."
SDKs
For building applications programmatically (not via MCP):
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 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.
License
MIT
Установка Fiber AI
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/fiber-ai/mcpFAQ
Fiber AI MCP бесплатный?
Да, Fiber AI MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Fiber AI?
Нет, Fiber AI работает без API-ключей и переменных окружения.
Fiber AI — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Fiber AI в Claude Desktop, Claude Code или Cursor?
Открой Fiber AI на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
Похожие MCP
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
автор: xuzexin-hzCompare Fiber AI with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории ai
