Fiber AI

ai.fiberPublished by fiber.aiOfficial publisherv1.0.0Updated Nov 3, 2026

Search companies, enrich contacts, and reveal emails and phones from your AI agent.

VerifiedStreamable HTTPWeb executableWeb Search & ScrapingBusiness & Commerce

Overview

AI-generated overview

Remote Fiber AI MCP server that lets an assistant search companies and people, enrich LinkedIn profiles, and reveal emails and phone numbers.

What you can do
  • Search companies by industry, location, size and funding, and search people by title, seniority and department
  • Enrich profiles and companies live from LinkedIn
  • Discover and call any of 100+ Fiber AI API endpoints through meta-tools or per-operation tools
  • Check account details such as credit balance, rate limits, auto top-up settings and API keys
  • Attach a card to a trial account and fetch the quickstart install script
When to use it
Useful when an assistant needs go-to-market or recruiting research inside an IDE or chat: prospecting lists, finding decision-makers, and turning a LinkedIn profile into contact details. Choose it if you already use Fiber AI data and want tool calls instead of writing scripts against the REST API.
Requirements
A remote Streamable HTTP endpoint; no local package. The V2 and Core servers need a Fiber AI API key, supplied as the x-api-key header, an Authorization Bearer header, or an apiKey field in the request body, typically read from a FIBER_API_KEY environment variable. The V3 server uses browser-based OAuth SSO instead. Stdio-only clients need an npx mcp-remote wrapper. Network access required.
Before you install
The API key is a paid-service credential: passing it in chat puts it in chat history, so prefer the x-api-key header for shared sessions or committed config files. Tools can list your API keys, read credit and top-up settings, and attach a payment card to a trial account. Searches and enrichment consume credits and send queries and profile identifiers to Fiber AI's servers.

Installation

In SourceWeft

  1. Open Fiber AI in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/ai.fiber%2Fmcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "fiber-ai": {
      "type": "http",
      "url": "https://mcp.fiber.ai/mcp/v2/"
    }
  }
}

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 (companySearch_tool, peopleSearch_tool, 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.

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.

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:

bash
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):

bash
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

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):

json
{  "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

bash
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:

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:

bash
codex mcp login fiber-ai-v3

The Codex IDE extension and the Codex app read the same ~/.codex/config.toml.

Gemini CLI

bash
gemini mcp add -t http -H "x-api-key: $FIBER_API_KEY" fiber-ai-v2 https://mcp.fiber.ai/mcp/v2gemini mcp add -t http fiber-ai-v3 https://mcp.fiber.ai/mcp/v3gemini 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):

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.

Visual Studio Code

Add to .vscode/mcp.json in your workspace (VS Code reads servers from the top-level servers key):

json
{  "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:

json
{  "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:

json
{  "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.

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

Available Tools

V2 Server (/mcp/v2)

Direct API tools — each Fiber AI endpoint is exposed as an individual tool:

ToolDescription
companySearch_toolSearch for companies by industry, location, size, funding, etc.
peopleSearch_toolSearch for people by title, seniority, department, etc.
profileLiveEnrich_toolLive-fetch a LinkedIn profile
companyLiveEnrich_toolLive-fetch a LinkedIn company
getOrgCredits_toolCheck your credit balance
getRateLimits_toolCheck your organization's rate limits
getAutoTopupSettings_toolGet auto top-up settings
getAllApiKeys_toolList your API keys
cardsAttach_toolAttach a card to a trial account
getQuickstartScript_toolGet 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:

ToolDescription
search_endpointsSearch for API endpoints by keyword
list_tag_packsList curated groups of endpoints to narrow the catalog
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.

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.

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 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.

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 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/sdk — GitHub
  • Python: pip install fiberai — GitHub

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.

License

MIT

Source: README.md at commit 2dbd42e

Tools

0
SourceWeft has not read this server's tools yet.

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declaredRequired10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

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