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

Enables AI assistants to read, search, and fully manage a Zotero library locally—organizing collections, editing items, uploading files, and managing notes, tags, and trash—through the local Zotero API without cloud sync.

Enables coding agents like Claude Code and Codex to offload boilerplate generation, summarization, and other bounded text tasks to local or cheap cloud LLMs, keeping the frontier agent in charge of judgment and code edits.

A thin MCP server that delegates lightweight tasks from Claude Code or any MCP-compatible client to local or cloud LLMs via LiteLLM, supporting models like Ollama and cloud APIs as subagents.

MCP server that delegates Claude Code subagents to alternative backends such as local models, DeepSeek, or AWS Bedrock, while keeping your Claude Code orchestrator session intact.

Optimizes token costs by intelligently delegating low-complexity tasks to local LLMs via LiteLLM, enabling cost-effective development workflows.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

A local MCP server that indexes codebases using Tree-sitter AST parsing and LanceDB, enabling AI models to search across repositories with sub-second latency.

MCP server for writing Markdown report fragments to files with path safety and SHA-256 verification.

Scans a repository for maintenance toil (flaky tests, expiring certificates, TODO rot, dead flags, etc.) and returns a prioritized queue with a credit ledger to track who cleared what.

An MCP server that enables safe, audited mutation of Google Ads campaigns—creating ads, ad groups, keywords, and assets or adjusting budgets and statuses—with a dry-run default and an optional guarded remove operation, plus read-only Keyword Planner ideas.

MCP server that provides AI assistants with real-time, current information about AI models from OpenAI, Anthropic, and Google, including pricing, capabilities, and context windows.

Blind multi-model councils with anonymous LLM seats and direct 1:1 chat as a local MCP server. Enables asking one question to get independent answers from multiple model CLIs, then blind scoring and reveal.

A TypeScript/JavaScript refactoring MCP server that uses the TypeScript compiler to perform safe, type-aware code transformations such as renaming, extracting functions, and organizing imports across your codebase.

Enables agents to search and deduplicate UK job vacancies across multiple boards, match them against local CVs, and submit complete applications through an automated browser with persistent logins and application memory.

Enables coding agents to inspect Python applications, research source and target models, and produce reviewable migration plans with evidence gates and evaluation before production code changes.

Provides a tool to fetch real-time cryptocurrency prices from the Binance API and logs server activity to file resources. It allows users to query crypto symbols and monitor MCP interactions through natural language interfaces.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Per-unit cost of 13 back-office tasks done by a person vs by software, in the US, Greece and Ukraine, with an official statistic behind every hourly wage. Bundled data, works offline.