"FIRST" matching MCP servers:

Windows-first MCP bridge for Kimi Code CLI, exposing code analysis, editing, sessions, and diagnostics as tools for AI agents.

Local-first code intelligence for AI coding assistants: MCP tools, symbol graph search, impact analysis, and auto-index watch for Cursor, Claude Code, and Codex.

Local-first code intelligence and safety layer for AI coding agents. MCP server exposes dependency graph, impact analysis, and AST-compressed repo context, backed by typed local memory, patch-scope safety gates, and git-independent transaction rollback.

An AI-agent-first framework for building MCP servers that deliver interactive React widgets directly within AI chat interfaces like ChatGPT and Claude. It includes automated visual testing and a zero-config local development environment designed for autonomous agent workflows.

Privacy-first, read-only repo intelligence for AI coding agents: scans local codebases and recommends MCP servers, repos, and research without sending data to the cloud.

LocalAnt is a local-first MCP gateway that lets ChatGPT control your PC through approved, permissioned tools for shell commands, file management, coding agents, browser automation, and more.

An MCP server that enhances Claude Code with evidence-first engineering, protocol gates, project-aware verification, auditable traces, and durable autonomous execution.

A local-first MCP gateway that reduces context overhead in coding-agent sessions by exposing only relevant tools and enforcing task-appropriate engineering gates, with privacy-first defaults and no network calls until explicitly enabled.

agent-delegate is an MCP-first delegation advisor for coding agents. It helps a main agent decide when to delegate read-only investigation, generate bounded subagent briefs, and summarize subagent results back into compact main-agent context.

Enables a local-first autonomous coding agent that plans, edits, and verifies code using LM Studio, Ollama, or llama.cpp models, with hardware-aware parallel sub-agents and optional frontier-model planning.

self-hosted development harness (Go engine + CLI + desktop, Linux first) · brief → requirements → spec → plan → build → review → release · verdicts are exit codes, never model opinions · local models first (llama.cpp, vLLM) beside any OpenAI-compatible or Anthropic endpoint · operable by humans or by other agents over MCP with recorded, attributed decisions

A local-first bridge for moving useful context between coding agents, indexing sessions and creating handoff packets for seamless agent switching.

A local-first MCP server for coordinating parallel AI coding sessions with tools like Claude Code and Codex in a single repository.

Local-first HTML review workspace for AI coding agents, enabling direct text and formatting edits, element comments, area annotations, and slide-aware review with durable agent handoffs.

Local-first MCP server that indexes all projects on your machine and provides coding agents with briefings about each project's stack, services, and run instructions, so they can start sessions with context across all repos. No cloud, no accounts, no telemetry.

Provides architectural memory for AI coding agents, enabling reuse of existing abstractions and advisory-first guidance on code placement and imports.

A secure, local-first MCP coding and computer-use harness for ChatGPT and Codex, enabling guarded file operations, durable terminals, Git review, local skills, and macOS computer control.

A local-first memory layer for coding agents to persist and retrieve project decisions, architecture context, and rules across multiple development sessions. It utilizes a three-tier memory model and hybrid retrieval to provide agents with durable, searchable context and a WebUI for human review.

SymbioPulse is an MCP-first context layer for AI coding agents that builds persistent project memory from directory fingerprints, task-to-file synapses, DNA constraints, and reusable skills, exposing it through MCP tools.

Local-first MCP toolkit that provides coding agents focused repository context via read_file, search_files, and edit_file tools, reducing token usage and task cost.