Heatherflux GitHub Issue MCP Server

The Heatherflux GitHub Issue MCP server turns a simple notes system into a fully‑integrated AI tool. It exposes resources, tools, and prompts that let an assistant like Claude read, write, and summarize notes stored on the server. Developers can plug this server into their AI workflow to give assistants persistent, structured memory that is both human‑readable and machine‑friendly.

The server solves the common problem of “memory” for AI assistants: without a dedicated store, each interaction starts from scratch. By representing notes as URIs with title, content, and metadata fields, the server gives assistants a reliable namespace to reference past conversations or data. The tool allows the assistant (or a user) to add new entries on demand, while the prompt aggregates all stored content and hands it to an LLM as a single, well‑formatted prompt. This eliminates repetitive context passing and lets the model focus on higher‑level reasoning.

Key capabilities include:

• Resource management: List and fetch notes via simple text‑based URIs, enabling fine‑grained access control or selective retrieval.
• Tool integration: The tool accepts a title and content, storing the note in server state—ideal for capturing meeting minutes or code snippets during a session.
• Prompt generation: pulls every note’s content into an embedded resource bundle, then returns a structured prompt ready for LLM summarization. This streamlines tasks like generating meeting summaries or project overviews.
• TypeScript foundation: The server is built in TypeScript, ensuring type safety and ease of extension for developers familiar with Node.js ecosystems.

Real‑world scenarios where this MCP shines include:

• Team collaboration: A project manager uses the server to collect action items during a stand‑up, then asks the assistant to produce a concise recap for stakeholders.
• Code review assistance: Developers create notes with pull‑request diffs or comments, and the assistant can summarize key changes for reviewers.
• Personal knowledge base: An individual captures insights from articles or lectures, then requests a monthly digest generated by the assistant.

Integration is straightforward: add the server to Claude Desktop’s configuration, and the assistant will automatically discover its resources, tools, and prompts. Once registered, any prompt can reference URIs, invoke , or ask for a summary without additional setup. The server’s lightweight design makes it ideal for prototyping or as a component in larger AI‑augmented workflows.