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AI"},"license":"MIT","homepage":"https://github.com/preceptai/precept-mcp-server#readme","keywords":["mcp","precept","preceptai","sales","leads","enrichment","model-context-protocol","company data","employee data","email data","phone data","contact data"],"repository":{"url":"git+https://github.com/preceptai/precept-mcp-server.git","type":"git"},"description":"Precept MCP Server for lead and company B2B intelligence","maintainers":[{"name":"johnbabat","email":"johnbabatola@gmail.com"}],"readme":"# Precept MCP Server\n\n> Expose [Precept's](https://preceptai.co.uk) B2B contact and company intelligence tools directly to AI assistants like **Claude Desktop**, **Cursor**, and **ChatGPT**.\n\nThis server implements the [Model Context Protocol (MCP)](https://modelcontextprotocol.io) and wraps Precept's core API. All operations are **non-blocking** — jobs return immediately with an `enrichment_id`, and results are polled via a separate status tool. This avoids LLM client timeouts on long running jobs.\n\nSupports dual-transport bootstrapping:\n\n- **`stdio`** — for local integrations (Claude Desktop, Cursor)\n- **Streamable HTTP** — for remote hosting (ChatGPT, enterprise agents)\n\n---\n\n## Tools\n\n| Tool                           | Description                                                                                                                                                                                          |\n| :----------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `precept_search_leads`         | Search for leads using natural language (e.g. _\"Marketing heads at SaaS companies in California\"_). Optionally enrich with verified emails, phone numbers, and AI insights. Returns a `jobId`.       |\n| `precept_enrich_leads`         | Enrich a specific list of contacts using LinkedIn URLs or name + company details. Returns verified emails, phones, professional summary, top problems, and strategic initiatives. Returns a `jobId`. |\n| `precept_get_company_insights` | Retrieve structured insights for specific companies — decision makers, technology stack, revenue, funding, employee counts, department ratios, and custom queries. Returns a `jobId`.                |\n| `precept_search_companies`     | Discover companies using natural language queries and optionally enrich with insights. Returns a `jobId`.                                                                                            |\n| `precept_get_job_status`       | Poll the status and retrieve results of any job. Poll every 4s for up to 150 attempts (~10m) while in progress and update user every 15 polls (~1m). Returns `processing` (with progress) or `completed` (with full data). |\n| `precept_check_credits`       | Check the remaining credit balance for your Precept account and server version status.                                                                                |\n| `precept_check_version`       | Check the running server version against the latest published release to see if a connector update is available.                                                     |\n\n### How It Works (Async Job Pattern)\n\n```\nUser → \"Find CTOs at fintech startups in London\"\n  ↓\nLLM calls precept_search_leads → returns { enrichment_id: \"job_123\" }\n  ↓\nLLM continuously polls precept_get_job_status(\"job_123\") every 4 seconds for up to 150 attempts (~10 minutes)\n  ↓\nLLM gives progress/status updates to the user every 15 polls (~1 minute)\n  ↓\nIf still processing → LLM keeps polling every 4 seconds\nIf completed → LLM receives full results with contact details and presents them to the user\nIf reaches 150 attempts (~10m) still in progress → LLM asks user to check back in a few minutes as it is taking longer than usual\n```\n\n---\n\n## Client Setup\n\nThe Precept MCP server is designed to run directly inside your LLM client.\n\n### Prerequisites\n\n- **Node.js** v20+\n- **Precept API Key** — generate one from the [Precept Developer Dashboard](https://app.preceptai.co.uk/developer)\n\n### 1. Claude Desktop\n\nAdd this config to your Claude Desktop configuration file (typically at `~/Library/Application Support/Claude/claude_desktop_config.json` on macOS or `%APPDATA%\\Claude\\claude_desktop_config.json` on Windows):\n\n```json\n{\n  \"mcpServers\": {\n    \"precept\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@preceptai/mcp-server\"],\n      \"env\": {\n        \"PRECEPT_API_KEY\": \"your_precept_api_key_here\"\n      }\n    }\n  }\n}\n```\n\n_(Make sure to completely restart/quit Claude Desktop after editing this file)._\n\n### 2. Cursor\n\nGo to **Settings** → **Features** → **MCP**:\n\n1. Click **+ Add New MCP Server**\n2. **Name:** `Precept` | **Type:** `command`\n3. **Command:** `npx -y @preceptai/mcp-server`\n4. Click **Save**\n5. Ensure your terminal has the `PRECEPT_API_KEY` environment variable set, or add it to a local `.env` file where Cursor is opened.\n\n### 3. Codex\n\nRun the following CLI command:\n\n```bash\ncodex mcp add precept --env PRECEPT_API_KEY=your_api_key_here -- npx -y @preceptai/mcp-server\n```\n\n_(Or add to `~/.codex/config.toml` under `[mcp_servers.precept]` if you prefer manual configuration)._\n\n---\n\n## Remote Setup: Streamable HTTP Mode\n\nFor remote deployment (e.g., ChatGPT Web/Desktop or hosted agents), run the server over Streamable HTTP:\n\n### 1. Configure Environment\n\nCreate a `.env` file in the project root:\n\n```env\nPRECEPT_API_KEY=your_precept_api_key_here\nMCP_TRANSPORT=http\nPORT=3000\nALLOWED_HOSTS=your-mcp-domain.com\n```\n\n### 2. Start Server\n\n```bash\nnpm start\n```\n\nThe server will expose a stateless MCP endpoint at `http://your-domain.com:3000/mcp`.\n\n---\n\n## Environment Variables\n\n| Variable          | Default               | Description                                                                                 |\n| :---------------- | :-------------------- | :------------------------------------------------------------------------------------------ |\n| `PRECEPT_API_KEY` | _(required)_          | Your Precept API key from the [Developer Dashboard](https://app.preceptai.co.uk/developer). |\n| `MCP_TRANSPORT`   | `stdio`               | Transport mode: `stdio` (local) or `http` (remote Streamable HTTP).                         |\n| `PORT`            | `3000`                | Port for HTTP mode.                                                                         |\n| `ALLOWED_HOSTS`   | `localhost,127.0.0.1` | Comma-separated allowed hosts for DNS rebinding protection (HTTP mode only).                |\n\n---\n\n## Credits & Pricing\n\nAll Precept API operations consume credits. Key costs:\n\n| Operation                   | Cost                      |\n| :-------------------------- | :------------------------ |\n| Lead Search (no insights)   | 0.1 credits/lead          |\n| Lead Search (with insights) | 1.1 credits/lead          |\n| Lead Enrichment             | 1 credit/lead             |\n| Contact Details (email)     | +1 credit/lead            |\n| Contact Details (phone)     | +10 credits/lead          |\n| Company Base Insight        | 1 credit/company          |\n| Custom Query                | 0.2 credits/query/company |\n| Decision Makers             | 0.5 credits/person/role   |\n| Technology Stack            | 2 credits/company         |\n| Revenue                     | 5 credits/company         |\n| Post Activity Filter        | +5 credits/lead           |\n\nSee the full [Precept Credits Documentation](https://docs.preceptai.co.uk/essentials/credits) for details.\n\n---\n\n## Links\n\n- [Precept Website](https://preceptai.co.uk)\n- [Precept API Documentation](https://docs.preceptai.co.uk)\n- [Developer Dashboard](https://app.preceptai.co.uk/developer)\n- [Model Context Protocol](https://modelcontextprotocol.io)\n\n---\n\n## License\n\nMIT\n","readmeFilename":"README.md"}