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Integration

MCP — Model Context Protocol

Drive outsend from your own Claude.ai, Claude Desktop, or any MCP-compatible client. Your subscription, your tokens.

Status: planned. The MCP server is on the roadmap; this page describes the intended endpoint shape so AI clients can plan against it. The release will be announced in the changelog.

The MCP integration exposes outsend as a remote MCP server that any MCP-compatible client can connect to: Claude.ai (custom connectors), Claude Desktop, Claude Code, Cursor, or any future client that speaks the protocol.

The user signs in once with their outsend account, and from then on the AI client can run searches, build pipelines, and read results — using the user's own LLM subscription (no outsend-side LLM cost).

How it will work

  1. The user opens settings in their MCP client (e.g. Claude.ai → Settings → Connectors → Add custom connector).
  2. They paste https://outsend.xyz/mcp and authenticate.
  3. The MCP server returns the list of available tools (see below).
  4. The model can call those tools on the user's behalf; each call hits the outsend API as that user.

Planned tools

Tool What it does
list_jobs List the user's recent jobs
get_job Fetch a job's status, counters, and a sample of its results
create_scrap_job Start a Google Maps extraction
create_enrich_job Start an enrichment on an existing job (emails, socials, …)
list_pipelines List the user's pipelines
create_pipeline Compose a pipeline from a description
run_pipeline Execute a saved pipeline
list_veilles List recurring veilles
create_veille Register an existing job as a recurring veille
get_signals Fetch the latest reputation signals from a veille run

Each tool's argument schema mirrors the corresponding API endpoint. In particular, create_pipeline takes the same portable envelope as the REST API ({schema_version, name, definition}), and the set of valid blocks plus their per-block config_schema is the contract already published at GET /api/pipelines/schema — the MCP server reuses it rather than defining its own.

Scope and limits

The MCP server inherits the user's normal permissions:

BYOK vs MCP

Pattern Where the chat lives Who pays the LLM tokens
BYOK Inside outsend.xyz The user, via a pasted API key
MCP Inside the user's existing AI client The user, via their subscription

The two patterns coexist. Pick BYOK if the assistant should live in the outsend UI; pick MCP if it should live wherever the user already works.

What's next