"Write TypeScript Code to Work with Local LLM" matching MCP servers:

Gemini-powered MCP server for automated code review, analysis, and documentation.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

An MCP server that connects AI assistants to a Neo4j graph database, enabling querying of movie data through tools like graph statistics, genre-based search, and movie details, along with advanced features such as LLM sampling and completions.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

This MCP server enables remote control and management of Claude Code agents, allowing you to execute missions, configure agent personalities, and integrate with other MCP tools.

Enables writing to Figma from MCP clients like Claude Code without a Figma Dev seat, using a local WebSocket relay and a Figma dev plugin.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

Enables local AI agents to generate and edit Figma designs via the Plugin API through a WebSocket relay, with no rate limits and all communication remaining local.

Provides comprehensive filesystem operations, text search/replace, image processing, and Tesseract OCR capabilities for AI agents via the Model Context Protocol.

Enables LLMs to interact with the AT Protocol ecosystem, including Bluesky, through natural language. Supports public data access without authentication and full write operations with authentication.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.

Enables local SOC 2 compliance work by scanning Infrastructure-as-Code, mapping findings to SOC 2 Trust Services Criteria, explaining risks in plain English, and drafting audit-ready documents without uploading files.

MCP server that injects verified FTC documentation and code examples into AI assistants, enabling teams to write correct, competition-ready Java robot code through natural language.

A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.

DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

Enables evaluation of AI-generated code across 45 specialized dimensions using deterministic pattern matching and optional LLM-powered deep review, acting as an independent quality gate.

Enables LLMs to access MCP protocol specifications and TypeScript SDK documentation with context-aware search and code templates for building custom MCP servers.

A TypeScript-based MCP server that enables users to interact with Prometheus metrics using PromQL queries and discovery tools. It allows LLMs to retrieve time-series data, metadata, alerts, and system status directly from a Prometheus instance.