"A local tool for counting characters in text" matching MCP servers:

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

MCP server that routes natural language requests to structured tool calls using a LoRA-tuned small language model, with built-in validation, retry, and fallback recovery.

Enables AI agents to drive a real Chrome browser using text-only accessibility-tree snapshots, with tools for navigation, interaction, and persistent task-space management.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

MCP router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables centralized proxy and orchestration of MCP servers, providing unified tool discovery, authentication, and secure request routing. It adds a human-in-the-loop approval gate for high-risk actions and audit logging.

Enables Claude Code to control Firefox through tools for tabs, navigation, clicks, typing, scrolling, screenshots, page reading, forms, JavaScript, and console/network logs.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

A configurable MCP gateway that runs multiple Streamable HTTP MCP servers and exposes all their tools through a single endpoint, enabling tool aggregation and routing for MCP clients.

Reference implementation of a Model Context Protocol server for integrating external APIs as agent tools. Includes built-in tools for weather, database queries, web search, and calculations, with authentication, rate limiting, and logging.

Enables users to describe an LLM fine-tuning workload once and receive ranked, task-aware GPU recommendations across a dozen cloud providers based on required VRAM/FLOPs, cost, and runtime. It surfaces the cheapest, fastest, and balanced options through MCP so coding assistants can plan training hardware without manual price comparison.

A framework for building hot-loadable MCP tools that feature conversational negotiation, graduated permissions, and zero-downtime updates. It enables persistent state continuity across server restarts and provides a hypothetical evaluation system for tool actions.

Enables Claude to fetch web pages from the user's own local network connection instead of AI datacenter IPs, including optional authenticated sessions, with verdicts for bot challenges, login walls, and other failures.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

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.

A local MCP server that lets Claude Code orchestrate Codex CLI and OpenCode CLI as sub-agents with strict security, concurrency, and output limits.

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Enables AI agent hosts to exchange durable, local sender/receiver messages through a SQLite mailbox exposed as MCP tools (connect, send, receive, reply, ack, status, disconnect), so a coordinator can dispatch commands and an executor can return results without model polling while idle. A configured host wake adapter is still required to turn an incoming event into an Agent turn.

Enables a cloud orchestrator to query a local Ollama model over Tailscale or a LAN as a side-channel for drafts, summaries, and other helper output, with tools to list available models and to redact text. Answers leaving the server are passed through output-only DLP that masks card numbers, IBANs, emails, phone numbers, API keys, and similar secrets before they reach the cloud.

A single MCP server that provides dynamic access to thousands of APIs through discovery and proxy, eliminating the need to install and configure multiple separate MCP servers.

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.

Enables Claude Code to offload mechanical development work—tests, git operations, pull requests, summaries, project search, code review, and browser or screen control—to local Ollama models with optional free cloud fallbacks. It returns concise results to reduce token usage while keeping execution on the user's own machine.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Enables AI clients to access many MCP servers through localhost HTTP endpoints, running each server once in a single Node process to avoid duplicated stdio spawns.

Enables AI coding agents to route tasks to local GPU models via a dynamic heuristic classifier, tracking real-time token dollar savings.