FlowMCP Server

FlowMCP Server

FlowMCP Server delivers a versatile, protocol‑agnostic bridge between AI assistants and external data sources. By exposing local or networked endpoints that adhere to the FlowMCP schema, it enables developers to expose a wide range of tools and resources—such as databases, APIs, or custom logic—to Claude or other MCP‑compatible assistants. The server abstracts away the intricacies of transport and activation, letting developers focus on defining schemas and workflows while ensuring secure, typed communication.

Solving the Integration Gap

Traditional AI assistants rely on static prompts or bespoke SDKs to access external services. This often forces developers into custom wrappers, duplicated logic, and fragile connections. FlowMCP Server solves this by providing a unified, standards‑compliant interface that translates schema definitions into concrete endpoints. Whether the assistant runs locally on a developer’s machine or in a cloud environment, it can discover and invoke tools via the same contract, eliminating the need for manual glue code.

Core Capabilities

• Dual‑mode operation: The server can run as a lightweight local stdin/stdout process (ideal for CLI testing) or expose HTTP/SSE endpoints over the network. This flexibility supports both rapid prototyping and production‑grade deployments.
• Transport agnosticism: Two transport protocols are supported—stateless POST requests and persistent Server‑Sent Events (). Developers can choose the model that best matches their latency, throughput, and state‑management requirements.
• Dynamic routing: Remote servers can expose multiple routes, each bound to its own set of schemas. This allows a single deployment to serve distinct APIs (e.g., , ) without code duplication.
• Activation payloads: FlowMCP Server leverages and helper methods to generate activation payloads that encode schema metadata, ensuring the assistant receives a fully typed contract.
• Simple deployment tooling: A helper parses command‑line arguments and environment variables, automatically configuring the chosen server type and exposing an Express app or local MCP instance.

Real‑World Use Cases

• Data‑centric assistants: Expose a database or spreadsheet as an MCP tool, letting the assistant query or update records through natural language commands.
• Micro‑service orchestration: Combine multiple internal services under a single MCP endpoint, allowing the assistant to trigger complex workflows without knowing each service’s API.
• Hybrid cloud stacks: Run a local server during development to test prompts, then switch to the remote HTTP/SSE variant for production without changing assistant code.
• Event‑driven agents: Use SSE to push real‑time updates (e.g., sensor data, stock prices) directly into the assistant’s context, enabling live decision making.

Standout Advantages

• Zero‑dependency I/O for the local server means it can run in minimal environments, such as CI pipelines or embedded devices.
• Stateless vs. persistent transport options give developers control over scalability and resource usage.
• Integrated schema management eliminates manual API documentation, ensuring the assistant always works against the latest contract.
• Open‑source and pluggable: The server is built on top of the FlowMCP framework, allowing easy extension with custom transports or authentication layers.

FlowMCP Server therefore streamlines the creation of AI‑enabled applications, providing a robust, protocol‑friendly foundation that scales from local prototypes to distributed services.