"A router for MCP (Model Context Protocol) tools" matching MCP servers:

Enables zero-auth agent workflows for email OTP extraction, KV checkpoints, webhook bins, wake timers, and clean URL-to-Markdown reading.

An event-driven MCP server that enables agents to share context streams, publish and subscribe to events, manage tasks, and follow protocols, keeping a fleet of agents mutually context-aware in real time.

A server built with mcp-framework that allows users to extend Claude's capabilities by adding custom tools that can be used through the Claude Desktop client.

An MCP server providing access to Telos, a philosophical AI mentor that combines rationalist thinking with stoic philosophy to offer personalized guidance and smart contract accountability on Solana.

A unified API server that enables interaction with multiple AI model providers like Anthropic and OpenAI through a consistent interface, supporting chat completions, tool calling, and context handling.

A server that implements the Model Context Protocol for Schwab API, allowing access to account information, positions, stock quotes, and order/transaction history designed for integration with Large Language Models.

Enables agent harnesses to make fast, confidence-aware tool selections using Jev, with planner fallback, hierarchical routing, and optional MCTS lookahead, exposed natively over MCP stdio.

A stateful gateway server for AI applications that solves the memory limitations of Large Language Models by maintaining separate conversation contexts for each user.

A conversational application server that integrates LLM capabilities via Ollama with vector memory context, supporting multiple users, sessions, automatic history summarization, and a plugin system for executing real actions.

A server exposing intelligent tools for enhancing RAG applications with entity extraction, query refinement, and relevance checking capabilities.

Universal HTTP 402 Micropayment Protocol & Autonomous Economic Settlement Engine for AI Agents on Base L2.

This server facilitates the invocation of AI models from providers like Anthropic, OpenAI, and Groq, enabling users to manage and configure large language model interactions seamlessly.

Enables agents and harnesses to offload routing, planning, review, batch decisions, and image localization to TypeSafe's Jev System One model via typed questions, supporting parallel workstreams and structured decisions.

Universal coordination hub for AI agents. Find collaborators, negotiate terms, form contracts, and build reputation through an MCP interface. Supports natural language search across agent networks.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

Enables local MCP clients to answer questions about the current browser page by capturing DOM context, routing them to fast or deep OpenAI models via a local model router, and optionally filling forms and submitting answers.

A durable MCP control plane for starting, observing, steering, continuing, cancelling, and handing off long-running coding agents, with bounded MCP calls and persistent worktrees.

Automatically selects the optimal LLM model for each task in Cursor IDE by analyzing query complexity, task type, and applying customizable routing strategies across 17 different AI models.

This MCP server enables LLM hosts to plan large tasks and delegate subtasks to specialized local CLI agents, such as Codex and Claude Code, using tools like delegate_task and get_agent_roster.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

Local MCP server for Bind Protocol — credential parsing, verification, and hashing tools for AI agents.

Persistent 3D/2D spatial world model MCP server for AI agents. Entity tracking, object permanence, AABB collision simulation & view frustum projection via local SQLite.

Enables orchestrator agents to route coding tasks to native CLI worker agents via MCP, providing tools for agent discovery, task submission, waiting, inspection, and cancellation.

Trust, identity, and reputation infrastructure for AI agents. Register agents with W3C DID (Ed25519), check EigenTrust reputation scores, submit peer attestations, search agents by capability, and verify IPFS-anchored audit trails. 11 tools.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Enables agents to retrieve their current identity from IDENTITY.md and route durable lessons, preferences, rules, and corrections to the appropriate standing file over MCP stdio.

Enables AI coding agents to make fast, zero-output-token decisions by evaluating context, diffs, logs, or options through the OpenRouter Decisions API using TypeSafe Jev, returning calibrated probabilities for binary, categorical, or scoring questions.

Security-enforcing MCP proxy that sits between an AI agent and any number of downstream MCP servers, intercepting every tool call through a capability-token policy gateway that can allow, deny, or escalate to human approval before the call reaches any real tool. It also exposes built-in operator tools for approval workflows, audit trail queries, token management, voice/HUD output, and hierarchical

Provides time intelligence, persistent memory and complete traceability for AI coding agents. Enables sophisticated activity tracking, timezone management, smart reminders, and cross-session continuity with support for both per-project and centralized storage modes.

Enables Claude Code as a team leader to delegate tasks to GPT and Gemini experts, supporting multi-LLM collaboration with tools for consultation, code review, design, and background execution.

Provides context management, task classification, and routing tools for small models (1B-12B) in production agentic workflows.

An MCP server that enforces explicit task ownership acceptance and requires a provenance tag (observed, reviewed, or reported) on every completion claim, preventing silent inheritance and unverified assertions in multi-agent systems.

Enables durable agent session transfer between machines by serializing state, provisioning sandboxes, and metering costs via MCP tools over a Postgres-backed state machine.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Resume-as-an-Agent (RAAA) or Portfolio-as-an-Agent (PAAA) allows Agents to talk to your resume, find out if you are available for work, and more. Use the MCP to allow recruiters, managers, and anyone with an agent to "talk" to your resume.

Enables schema-validated, sandboxed access to 34 Python-powered tools across Pillow, requests, pypdf, pandas, openpyxl, and python-docx, plus an autonomous ReAct converter agent that can grow the catalog by requirement and self-repair at runtime. It also provides a control console and hardened Docker deployment for secure MCP client integration.

A persistent memory and context management system for AI CLI tools that utilizes a three-layer architecture and semantic search to prevent context loss between sessions. It provides time-aware orientation and smart memory routing to help AI agents maintain project knowledge and architectural decisions.

Enables MCP-aware clients to use a reliable multi-agent tool system with tiered model routing, schema-validated decisions, and graceful tool degradation, allowing small models to handle complex tasks.

Enables AI agents to keep skill catalogs outside the main LLM context and load only task-relevant SKILL.md instructions via a single MCP tool, reducing context overhead.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.