"Frappe" matching MCP servers:

Enables AI agents to explore and operate Frappe Framework, ERPNext, and HRMS sites at runtime by discovering installed apps, permission-visible DocTypes, schemas, records, child tables, reports, workflows, workspaces, print formats, files, and translations through the authenticated Frappe session. It also supports guarded create, update, delete, submit, cancel, and workflow actions alongside standard DocType, Custom Field, Property Setter, Client Script, permission, and app-customization export operations, each gated by preview and explicit confirmation.

Enables Frappe Framework apps to expose Python functions as MCP tools over a Streamable HTTP endpoint on WSGI-based servers, so LLM clients can call app logic through JSON-RPC. Tool schemas are inferred automatically from type annotations and Google-style docstrings, with OAuth2-based authentication.

Enables existing Frappe Framework applications to serve Streamable HTTP MCP endpoints, register Python functions as tools, and generate tool input schemas from signatures and docstrings.

Lets Frappe Framework apps expose their functions as MCP tools over a Streamable HTTP endpoint, with tool schemas inferred from type annotations and docstrings, plus OAuth2-based authentication. Works with Werkzeug/WSGI-based servers so existing synchronous Python web apps can serve LLM-callable tools without an ASGI stack.

Enables Frappe Framework apps to act as Streamable HTTP MCP servers, exposing decorated Python functions as tools that LLMs can call, with input schemas generated automatically from type annotations and docstrings. It integrates with the framework's WSGI-based request handling and OAuth2 authentication.

Enables Frappe Framework applications to act as Streamable HTTP MCP servers, exposing registered Python functions as tools that MCP clients and LLMs can discover and call.

Enables applications built on the Frappe Framework to expose registered tools as a Streamable HTTP MCP server over a Werkzeug/Frappe REST endpoint, with automatic input schema generation from Python function signatures and docstrings.

Enables a Frappe Framework app to serve as a Streamable HTTP MCP server, exposing Python functions as tools with JSON-RPC handling wired into an existing WSGI endpoint. Tool descriptions and input schemas are inferred automatically from type annotations and Google-style docstrings, so apps can be made LLM-callable with minimal configuration.

Enables Frappe Framework apps to function as Streamable HTTP MCP servers by exposing registered Python functions as tools for MCP clients over a WSGI-compatible endpoint.

Enables Frappe Framework apps to function as Streamable HTTP MCP servers and expose registered Python functions as callable tools for MCP clients.

Enables Frappe Framework apps to act as Streamable HTTP MCP servers, exposing registered Python functions as callable tools for LLM clients.

Enables applications built on the Frappe Framework to serve MCP tools over Streamable HTTP, letting LLM clients call registered Python functions through a Werkzeug-compatible endpoint.

Enables Frappe Framework apps to expose registered Python functions as MCP tools over a Streamable HTTP endpoint, allowing MCP clients to invoke app functionality.

Enables AI assistants to interact with ERPNext/Frappe instances through the REST API, allowing document management, report execution, and DocType operations using natural language.