aidemd-mcp/server
by Various
MCP server that teaches any AI agent the AIDE spec methodology — progressive disclosure specs alongside code
MCP
aidemd-mcp/server
Added 1 June 2026
Overview
An MCP server that implements the AIDE spec methodology, enabling AI agents to work with progressive disclosure specifications alongside code. It provides a standardized interface for agents to read, write, and manage spec files that unfold detail incrementally. The server is written in TypeScript and designed to integrate into AI coding workflows.
Best for
Best for
Developers building AI-assisted coding workflows that follow the AIDE progressive disclosure spec methodology
Use cases
- Teaching AI agents to follow progressive disclosure specification patterns
- Managing AIDE spec files alongside code in agent-assisted development
- Integrating structured spec methodology into MCP-compatible AI coding tools
Notes
An MCP server that implements the AIDE spec methodology, enabling AI agents to work with progressive disclosure specifications alongside code. It provides a standardized interface for agents to read, write, and manage spec files that unfold detail incrementally. The server is written in TypeScript and designed to integrate into AI coding workflows.
2 stars on GitHub. Last updated 2026-05-22. Licensed MIT.
Use cases
- Teaching AI agents to follow progressive disclosure specification patterns
- Managing AIDE spec files alongside code in agent-assisted development
- Integrating structured spec methodology into MCP-compatible AI coding tools
Pros
- Enforces a structured spec methodology that reduces ambiguity for AI agents
- Open source with TypeScript implementation, easy to extend or audit
- Lightweight MCP server, straightforward to self-host
Cons
- Very early stage with only 2 GitHub stars, limited community or support
- Narrowly scoped to the AIDE spec methodology, not general-purpose
- Requires AI agents to be MCP-aware, which is still a nascent ecosystem
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Enforces a structured spec methodology that reduces ambiguity for AI agents
- Open source with TypeScript implementation, easy to extend or audit
- Lightweight MCP server, straightforward to self-host
Cons
- Very early stage with only 2 GitHub stars, limited community or support
- Narrowly scoped to the AIDE spec methodology, not general-purpose
- Requires AI agents to be MCP-aware, which is still a nascent ecosystem
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