Fiber AI

AI 与智能体

by fiber-ai

让你的 AI agent 搜索公司、丰富联系人信息,并挖掘邮箱与电话号码等线索。

什么是 Fiber AI

让你的 AI agent 搜索公司、丰富联系人信息,并挖掘邮箱与电话号码等线索。

README

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:

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:

ServerURLAuthBest For
V2https://mcp.fiber.ai/mcp/v2API keyAuto-generated direct tools for the top ~10 priority operations (api_companySearch, api_peopleSearch, etc.)
V3https://mcp.fiber.ai/mcp/v3OAuth (SSO)Direct tools for every public operation with compact descriptions; the model can call or expand any tool on demand
Corehttps://mcp.fiber.ai/mcpAPI key5 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:

bash
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:

code
cursor://anysphere.cursor-deeplink/mcp/install?name=FiberAI-V2&config=eyJ1cmwiOiJodHRwczovL21jcC5maWJlci5haS9tY3AvdjIifQ==

Install Core:

code
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:

bash
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:

bash
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:

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

bash
codex mcp add fiber-ai --url https://mcp.fiber.ai/mcp/v2

Or add to ~/.codex/config.toml:

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:

code
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:

json
{
  "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):

json
{
  "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:

json
{
  "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:

json
{
  "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> (or Authorization: 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:

ToolDescription
api_companySearchSearch for companies by industry, location, size, funding, etc.
api_peopleSearchSearch for people by title, seniority, department, etc.
api_individualRevealSyncReveal work email and phone for a LinkedIn profile
api_companyLiveFetchGet live LinkedIn data for a company
api_personLiveFetchGet live LinkedIn data for a person
api_getOrgCreditsCheck your credit balance

Core Server (/mcp)

Meta tools for dynamic endpoint discovery:

ToolDescription
search_endpointsSearch for API endpoints by keyword
list_all_endpointsList all available API endpoints
get_endpoint_details_fullGet full schema details for an endpoint
call_operationCall 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.

code
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.

json
{
  "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:

json
"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.

json
"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 <a company you care about> 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):

  • TypeScript: npm install @fiberai/sdkGitHub
  • Python: pip install fiberaiGitHub

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

常见问题

Fiber AI 是什么?

让你的 AI agent 搜索公司、丰富联系人信息,并挖掘邮箱与电话号码等线索。

相关 Skills

Claude接口

by anthropics

Universal
热门

面向接入 Claude API、Anthropic SDK 或 Agent SDK 的开发场景,自动识别项目语言并给出对应示例与默认配置,快速搭建 LLM 应用。

想把Claude能力接进应用或智能体,用claude-api上手快、兼容Anthropic与Agent SDK,集成路径清晰又省心

AI 与智能体
未扫描165.9k

RAG架构师

by alirezarezvani

Universal
热门

聚焦生产级RAG系统设计与优化,覆盖文档切块、检索链路、索引构建、召回评估等关键环节,适合搭建可扩展、高准确率的知识库问答与检索增强应用。

面向RAG落地,把知识库、向量检索和生成链路系统串联起来,做架构设计时更清晰,也更少踩坑。

AI 与智能体
未扫描23.7k

多智能体架构

by alirezarezvani

Universal
热门

聚焦多智能体系统架构设计,梳理 Supervisor、Swarm、分层和 Pipeline 等模式,覆盖角色定义、通信协作与性能评估,适合规划稳健可扩展的 AI agent 编排方案。

帮你系统解决多智能体应用的架构设计与协同编排难题,适合构建复杂 AI 工作流,成熟度高、社区认可也很亮眼。

AI 与智能体
未扫描23.7k

相关 MCP Server

顺序思维

编辑精选

by Anthropic

热门

Sequential Thinking 是让 AI 通过动态思维链解决复杂问题的参考服务器。

这个服务器展示了如何让 Claude 像人类一样逐步推理,适合开发者学习 MCP 的思维链实现。但注意它只是个参考示例,别指望直接用在生产环境里。

AI 与智能体
89.1k

知识图谱记忆

编辑精选

by Anthropic

热门

Memory 是一个基于本地知识图谱的持久化记忆系统,让 AI 记住长期上下文。

帮 AI 和智能体补上“记不住”的短板,用本地知识图谱沉淀长期上下文,连续对话更聪明,数据也更可控。

AI 与智能体
89.1k

by deusdata

热门

持久化的代码库知识图谱,可跨会话保留上下文,在 session 重启或上下文压缩后仍能继续使用。

专治 AI 编程助手“会话失忆”,把代码库沉淀为持久知识图谱,重启或压缩上下文后也能无缝续上开发状态。

AI 与智能体
36.7k

评论