@preceptai/mcp-server
Advanced tools
Expose Precept's enterprise B2B lead discovery, company intelligence, signal monitoring, and automated LinkedIn outreach directly inside AI assistants like Claude (Web & Desktop), ChatGPT, Cursor, and Codex.
This server implements the open Model Context Protocol (MCP) specification. It enables LLMs to search millions of verified decision makers, enrich contact details via a 140+ provider waterfall, monitor hiring and career moves, and orchestrate automated outreach campaigns without leaving the conversation.
Precept MCP Server supports dual-transport bootstrapping:
stdio (Local CLI): Standard input/output transport for local developer tools (Claude Desktop, Cursor, Codex, CLI agents) powered by npx -y @preceptai/mcp-server.All heavy data operations are non-blocking and asynchronous: jobs immediately return an enrichment_id (jobId), and the assistant polls progress via precept_get_job_status until complete. This prevents LLM client timeouts on deep web research and waterfall data lookups.
Precept MCP Server exposes 13 specialized tools organized across lead discovery, account intelligence, signal subscriptions, outreach automation, and system utilities:
| Tool | Description |
|---|---|
precept_search_leads | Search and discover business leads using natural language queries (e.g. "Marketing heads at SaaS companies in California with 50-200 employees"). Supports optional waterfall contact enrichment (verified emails and direct dials) and AI-generated prospect profiles. |
precept_get_leads_from_post_search | Discover high-intent prospects actively engaging (posting, commenting, reacting) with specific topics on LinkedIn over the past 24 hours, week, or month. |
precept_enrich_leads | Enrich a specific list of contacts using LinkedIn URLs or name + company details. Delivers verified emails, phone numbers, professional summary, top problems, and strategic initiatives. |
| Tool | Description |
|---|---|
precept_search_companies | Discover accounts matching specific criteria (industry, headcount, geography, revenue, recent funding, tech stack). Optionally extracts key department heads and employee breakdowns. |
precept_get_company_insights | Retrieve deep structured intelligence on target accounts: decision makers across 40 canonical departments, installed technologies, funding history, revenue, employee growth trends, and department ratios. |
| Tool | Description |
|---|---|
precept_job_posting_subscriptions | Monitor real-time hiring triggers on a 7–30 day schedule. Supports natural language queries ("active AI or ML jobs in healthcare") or monitoring up to 100 target accounts. Automatically extracts relevant decision makers for each open role with zero duplicate billing. |
precept_lead_subscriptions | Track up to 150 target decision makers per organization for career moves: job changes, internal promotions, title updates, and new LinkedIn posts. |
| Tool | Description |
|---|---|
precept_get_extension_status | Checks if the user's Precept Chrome Extension is installed and active. Required before launching outreach or dispatching messages. |
precept_campaign_queue | Queue discovered leads directly into automated LinkedIn outreach campaigns. Supports FIFO queue discipline, progress tracking, rate-limit safety pauses, resuming, pausing, and archiving campaigns. Runs safely in Chrome background without needing Precept or LinkedIn tabs open. |
precept_linkedin_messages | Dispatches 1-on-1 direct messages or connection request notes via LinkedIn with automated delivery status verification and error diagnostics. |
| Tool | Description |
|---|---|
precept_get_job_status | Polls progress and retrieves complete structured results for any async search or enrichment job. Returns progress percentages while processing and full datasets upon completion. |
precept_check_credits | Checks remaining account credit balance and connector version status before initiating operations. |
precept_check_version | Validates running connector version against the latest release to check if updates are available. |
User: "Find 20 VP of Sales at fintech companies in New York"
│
▼
LLM calls `precept_check_credits` → verifies sufficient balance
│
▼
LLM calls `precept_search_leads` → returns { enrichment_id: "job_94827" }
│
▼
LLM polls `precept_get_job_status("job_94827")` every 4s (up to 150 attempts / 10m)
│ Updates user with progress every ~1 minute
▼
Job completes → LLM presents full structured table/artifact with contacts
│
▼
Follow-up: LLM offers to enrich phone numbers or queue LinkedIn outreach
pt_...).Both Claude (Web & Desktop apps) and ChatGPT connect to Precept via remote Streamable HTTP using OAuth 2.1. Once added in your Claude account, connectors automatically sync across web, desktop, and mobile:
Precept AIhttps://precept-mcp-server-production.up.railway.app/mcpclaudehttps://precept-mcp-server-production.up.railway.app/mcpDeveloper CLI agents and IDEs execute the server locally over stdio via npx using your API key:
Run the following in your terminal:
claude mcp add --env PRECEPT_API_KEY=pt_your_api_key_here precept -- npx -y @preceptai/mcp-server
(Supports --scope user to make Precept available globally across all projects, or --scope project to save into .mcp.json).
Prefer the hosted connector instead? Claude Code also supports remote servers:
claude mcp add --transport http precept https://precept-mcp-server-production.up.railway.app/mcp
Then run /mcp inside Claude Code to complete authorization.
Preceptcommandnpx -y @preceptai/mcp-serverPRECEPT_API_KEY=pt_your_api_key_here in your environment or workspace .env.stdio mode)If you prefer running the server locally in Claude Desktop instead of using the remote OAuth connector, add this to claude_desktop_config.json:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": {
"precept": {
"command": "npx",
"args": ["-y", "@preceptai/mcp-server"],
"env": {
"PRECEPT_API_KEY": "pt_your_api_key_here"
}
}
}
}
Run:
codex mcp add precept --env PRECEPT_API_KEY=pt_your_api_key_here -- npx -y @preceptai/mcp-server
To host your own remote Streamable HTTP server:
git clone https://github.com/johnbabat/precept-mcp-server.git
cd precept-mcp-server
npm install
npm run build
Configure environment variables in .env:
PORT=3000
MCP_TRANSPORT=http
ALLOWED_HOSTS=your-domain.com
JWT_SECRET=your-random-32-character-secret
PRECEPT_API_URL=https://api.preceptai.co.uk
Start the server:
npm start
The endpoint will be available at http://your-domain.com:3000/mcp with full OAuth 2.1 endpoints at /authorize and /token.
| Variable | Transport | Default | Description |
|---|---|---|---|
PRECEPT_API_KEY | stdio | (required for stdio) | Your Precept API key (pt_...). |
MCP_TRANSPORT | Both | stdio | Transport type: stdio (local CLI) or http (remote streamable HTTP). |
PORT | http | 3000 | Port for the HTTP server. |
ALLOWED_HOSTS | http | localhost,127.0.0.1 | Comma-separated allowed hostnames for DNS rebinding protection. |
JWT_SECRET | http | (auto-generated) | Secret for signing OAuth tokens. Set this in production — if omitted, a random secret is generated and all connected users are logged out on every restart. |
ALLOWED_REDIRECT_DOMAINS | http | (see source) | Comma-separated domains allowed as OAuth redirect_uri targets (e.g. Claude and ChatGPT callback domains). |
REDIS_URL | http | (optional) | Redis connection string for persistent distributed auth code storage. Defaults to in-memory store. |
PRECEPT_API_URL | Both | https://api.preceptai.co.uk | Core Precept API endpoint. |
Precept API uses a credit-based model for data operations:
| Operation | Cost |
|---|---|
| Lead Search (basic profile) | 0.1 credits / lead |
| Lead Search with AI Insights | 1.1 credits / lead |
| Lead Enrichment (existing contact) | 1.0 credit / lead |
| Verified Work Email | +1.0 credit / lead |
| Verified Direct Phone Number | +10.0 credits / lead |
| Both Email & Phone | +11.0 credits / lead |
| Company Search / Base Insights | 1.0 credit / company |
| Custom AI Company Query | +0.2 credits / query / company |
| Company Decision Makers | 0.5 credits / person |
| Company Tech Stack | 2.0 credits / company |
| Company Revenue / Funding | 5.0 credits / company |
| Job Posting Subscription Monitoring | 0 credits for search; 0.5 credits / discovered decision maker |
| Post Activity Filter | +5 credits / lead |
Full documentation on credit policies is available at docs.preceptai.co.uk.
MIT © Precept AI
FAQs
Precept MCP Server for lead and company B2B intelligence
The npm package @preceptai/mcp-server receives a total of 52 weekly downloads. As such, @preceptai/mcp-server popularity was classified as not popular.
We found that @preceptai/mcp-server demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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