The D50 MCP server
Give any AI agent 100+ real actions across sales, marketing, content, and hiring. The D50 Model Context Protocol server exposes the entire platform — the same tools a human uses in the app — to Claude, Cursor, or any MCP-compatible client.
The server speaks the MCP 2025-03-26 Streamable-HTTP transport. One endpoint, JSON-RPC over HTTPS:
| Method | Path | Purpose |
|---|---|---|
POST | /api/mcp | JSON-RPC requests (initialize, tools/list, tools/call) |
GET | /api/mcp | SSE stream for server notifications |
DELETE | /api/mcp | Terminate the session |
GET | /api/mcp/health | Health check (no auth) |
Connect a client
Claude Desktop / Claude Code
Add D50 to your MCP config with an API key from app.d50.ai → Settings → API keys:
{
"mcpServers": {
"d50": {
"type": "http",
"url": "https://app.d50.ai/api/mcp",
"headers": { "Authorization": "Bearer d50_live_…" }
}
}
}
Claude.ai (custom connector)
Add https://app.d50.ai/api/mcp as a custom connector and authorize via OAuth — D50 implements the MCP OAuth 2.0 flow (/api/mcp/oauth/*), so no manual key handling.
Cursor / any MCP client
Point the client at the same HTTP URL with the Authorization: Bearer header. The agent calls tools/list and discovers every tool automatically.
Authentication
- Bearer API keys — every call carries
Authorization: Bearer d50_…. Keys are created per-agent in the app, stored only as a SHA-256 hash, and can carry an expiry. - Tool scopes — a key can be unrestricted (
*) or limited to a named set of tools, so an agent only gets the actions you grant it. - OAuth 2.0 — for hosted clients (Claude.ai), the standard authorization-code flow is supported.
- Sessions — stateful, 30-minute TTL; team membership is validated at auth time so multi-tenant data stays correctly scoped.
Tool catalog — 100+ tools
The full surface of the platform, grouped by capability — a representative selection per category below. Every tool is callable over MCP and the REST API.
CRM · selected tools
Lead Generation · selected tools
Communication & Outreach · selected tools
Content & Media · selected tools
Scraping & Research · selected tools
Funnels & Pages · selected tools
SEO & Competitive Intel · selected tools
Knowledge & Memory · selected tools
AI Agents · selected tools
Recruitment · selected tools
Calendar & Booking · selected tools
Ads · selected tools
YouTube Pipeline · selected tools
Billing & Account · selected tools
Example agent session
An agent finds prospects, reveals contacts, and starts an AI call — three tool calls, one wallet:
// 1) find prospects
search_leads({ industry: "saas", country: "AE", limit: 25 })
// 2) reveal the best one's contact (bills 0.30 credits)
reveal_lead({ leadId: "lead_…" })
// 3) let an AI agent call and book a meeting (bills per minute)
initiate_ai_call({ to: "+9715…", goal: "book_meeting", agent: "sdr" })
That is the difference between an AI that can talk and an AI that can act. Start free and point your agent at D50.