MCP delivery adapter plugin for functualize — exposes jobs as MCP tools via FastMCP
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"functualize-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# functualize-mcp > **Status: Published** — Independently installable from PyPI. MCP delivery adapter plugin for functualize — exposes jobs as MCP tools via FastMCP. External AI agents (Goose, Claude, Cursor) can discover and invoke functualize jobs through the standardized [Model Context Protocol](https://modelcontextprotocol.io/) interface without any manual wiring. ## Installation ```bash pip install functualize-mcp ``` ## Quick Start ```python from functualize_mcp import JobToolTranslator, MCPToolDef, SchemaExporter # Translate a job descriptor into an MCP tool definition translator = JobToolTranslator() tool_def = translator.translate(my_job_descriptor) print(tool_def.name, tool_def.description) # Export all job schemas as OpenAI function calling JSON exporter = SchemaExporter(translator) openai_json = exporter.export_openai(descriptors) ``` ## Features - Automatic job-to-tool translation with JSON Schema input generation from config models - Dual transport support: stdio (default) and HTTP+SSE for networked agents - Job visibility filtering via include/exclude tags and job name exclusion lists - Multi-format schema export: JSON (MCP), Markdown, OpenAI function calling, TypeScript - Multi-server management: start, list, and stop background HTTP servers - Workflow inspection and advancement tools for paused workflow steps - Async job execution with polling via `run_job_async` / `get_execution_status` - AI outbound gate strategy for workflow checkpoint serialization ## API Reference Public classes and functions exported by this plugin: - `MCPAdapterPlugin` — Plugin entry point implementing the AdapterPlugin protocol; registers MCP tools at boot - `MCPConfig` — Pydantic configuration model controlling transport, port, host, tag filters, and management features - `MCPServer` — FastMCP wrapper that discovers jobs, registers tools, and serves via stdio or HTTP+SSE - `JobToolTranslator` — Translates JobDescriptors into MCPToolDef instances using docstrin…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.