Aifp
Enforce functional-programming rules and database-backed project management while an AI agent maintains your codebase.
Overview
AIFP is a MCP server for the Build phase that provides database-driven FP enforcement and project management for AI-maintained codebases.
What is this MCP server?
- Database-driven functional programming enforcement for agent-written code
- Project management primitives for AI-maintained repositories
- PyPI package aifp with uvx stdio MCP transport
- Targets codebases where the agent is the primary maintainer
- Registry version 0.1.1 from aryanduntley/AIFP on GitHub
- PyPI identifier aifp with uvx runtimeHint
What problem does it solve?
Agents rewrite code without persistent FP discipline or a real task system, so tech debt compounds invisibly.
Who is it for?
Solo developers running agent-first maintenance on FP-leaning stacks who want structure beyond ad-hoc prompts.
Skip if: Casual vibe-coding without interest in functional style or database setup.
What do I get? / Deliverables
Rules and PM state live in a database the MCP server exposes so agent edits stay aligned with enforced FP and tracked work.
- MCP-accessible FP enforcement tied to persistent storage
- Project management hooks for AI-driven maintenance
- stdio MCP server from PyPI aifp 0.1.1
Recommended MCP Servers
Journey fit
How it compares
FP enforcement plus PM MCP, not a generic todo skill or linter-only integration.
Common Questions / FAQ
Who is AIFP for?
Builders using AI agents as ongoing maintainers who want FP guardrails and DB-backed project tracking.
When should I use AIFP?
When you are scaling agent-written changes and need persistent rules and task state outside the chat window.
How do I add AIFP to my agent?
Configure the PyPI MCP server aifp with uvx and stdio transport in your MCP client per the registry entry.