Fg Mcp Server

Overview

The Fg MCP Server brings the Model Context Protocol (MCP) to a serverless environment on FunctionGraph, enabling AI assistants such as Claude to access external resources and tools without the overhead of managing traditional servers. By packaging popular MCP implementations into a lightweight, event‑driven deployment, the server eliminates infrastructure concerns—no provisioning, scaling, or maintenance is required beyond a simple FunctionGraph function. This makes it an attractive option for teams that need rapid, cost‑effective access to MCP capabilities in production or experimentation.

At its core, the server exposes a set of MCP endpoints that allow an AI client to retrieve resources, invoke tools, fetch prompt templates, and perform sampling operations. Developers can define custom tool handlers or leverage pre‑built ones, then register them with the server so that an AI assistant can call these tools directly from within a conversation. The server handles request routing, authentication, and response formatting according to the MCP specification, ensuring seamless communication between the assistant and the underlying services.

Key features include:

• Serverless Deployment: Runs on FunctionGraph, automatically scaling with traffic and billing only for actual execution time.
• Modular Tool Integration: Supports plugging in arbitrary tool logic, from simple HTTP calls to complex data‑processing pipelines.
• Resource Management: Exposes static or dynamic content (e.g., knowledge bases, configuration files) that assistants can query on demand.
• Prompt Reuse: Stores reusable prompt templates, allowing consistent wording and context across interactions.
• Sampling Control: Provides fine‑grained sampling parameters to shape the assistant’s responses, such as temperature or token limits.

Typical use cases span from building a chatbot that can browse the web, query databases, or trigger CI/CD pipelines, to creating an AI‑powered support desk that pulls from internal knowledge bases. In a real‑world scenario, a developer might deploy the Fg MCP Server to FunctionGraph, register a tool that calls an internal REST API for ticket status, and then have Claude automatically fetch updates during a conversation. The server’s lightweight nature means that such integrations can be iterated quickly, with minimal operational overhead.

What sets the Fg MCP Server apart is its combination of serverless convenience and full MCP compliance. By abstracting away the complexities of hosting an MCP server, it allows developers to focus on crafting tool logic and conversational flows. The tight integration with FunctionGraph also means that existing AWS‑compatible services—such as RDS, S3, or Lambda—can be wired into the tool set with minimal friction. For teams that need to prototype AI‑enabled workflows or deploy production‑grade assistants without investing in persistent infrastructure, this server offers a pragmatic, scalable solution.