"An overview of REST (Representational State Transfer)" matching MCP servers:

Single source of truth and control for agent-operated companies, managing business state with deterministic policy enforcement, seat identity, and hash-chained audit trail.

An MCP-native state sidecar that externalises workflow state for distributed agent deployments.

Provides state and log management tools designed for long-lived AI agents that may be interrupted and resumed. It enables tracking agent progress and maintaining an append-only event history to ensure continuity across multiple sessions.

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

A meta-server that aggregates multiple MCP servers into a single interface, reducing token usage by 98%+ through progressive tool discovery and direct code execution that processes data between tools without consuming context window space.

A multi-agent orchestration system that enables multiple Claude instances to collaborate through a centralized hub with a shared workspace and real-time communication. It features integrated task management, role assignment, and persistent memory to facilitate complex, synchronized agent workflows.

Enables MCP-compatible agents to arbitrate typed state-action schemas, dispatch routine actions deterministically, and apply pre-escalation filters that reduce unnecessary frontier LLM calls. It supports low-latency, schema-enforced routing with safety guardrails and local-first memory retention.

Enables AI agents to persist and restore checkpoint state, supporting crash recovery and replay for LangGraph-based workflows.

Enables multi-agent systems to share and coordinate a common state space over MCP, detecting concurrent mutation race conditions, synchronizing state through vector clocks, and resolving conflicting decisions via consensus arbitration. Also supports deterministic policy validation and cryptographic state hashing with zero external dependencies.

Enables AI agents to commit stateful workflow checkpoints by calculating state hashes and rollback points through the Model Context Protocol. It provides deterministic, dependency-free checkpoint management for autonomous agent execution.

Enables AI agents to arbitrate typed state-action schemas and dispatch deterministic actions locally, so routine or reflexive decisions are resolved in sub-millisecond fashion instead of incurring expensive frontier-LLM calls. It also applies token-saving pre-escalation filters, escalating only ambiguous or multi-hop plans to larger models while enforcing reversible execution checkpoints, strict token budgets, and local-first memory retention.

Enables AI agents to capture and commit stateful workflow checkpoints during autonomous execution, computing deterministic state hashes and rollback points. It runs as a zero-dependency Python MCP server that plugs into Claude Desktop, Cursor, and other MCP-compliant clients for reliable, low-latency checkpoint management.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables AI assistants to maintain continuity across sessions by tracking named work lanes, structured handoffs, artifacts, and reusable routines so work can pick up where it left off.

An MCP Server that provides access to League of Legends statistics via the SportData.io API, allowing agents to query and analyze LoL competitive gaming data.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Enables AI assistants to interact with the QuantConnect cloud platform for algorithmic trading. Supports creating and managing trading strategies, running backtests, deploying live algorithms, and performing comprehensive trading operations through the QuantConnect API.

Enables Claude Code instances to discover each other on a local machine and exchange messages instantly, with a broker that coordinates triage and delegation across a peer mesh.

An MCP server that enables AI agents to execute real-world actions through 10 specialized engines covering authenticated API calls, browser automation, visual QA, shell commands, file operations, job scraping, and parallel task execution.

Shared versioned state for multi-agent AI workflows. An MCP server.

Context window usage estimation for AI coding agents via MCP, enabling proactive state preservation before compaction.

Lets an AI agent check its own Claude and Codex usage limits — used percentages and exact reset times for session and weekly windows — so it can plan long-running work around resets instead of dying mid-task. It reads local, credential-free sources by default, always reports which source answered, and ships a hook that pushes quota state into context automatically.

Agent Connectivity Gateway — turn any authenticated API into an MCP Server. Self-hosted reverse proxy with OAuth 2.0/OIDC credential injection, per-agent isolation, NAT traversal for localhost services, and REST-to-MCP auto-wrap from OpenAPI specs. Works with Claude Code, Cursor, Codex. Rust.

A hardened, self-hosted MCP server that lets AI agents query and govern an Infraveil control plane in-loop, reading state and filing deploy/remediation requests that require human approval.

Enables AI agents to drive a Chromium browser over MCP, reading pages as a numbered list of controls and performing actions like clicking, filling forms, and asserting page state without screenshots or API keys.

Lets any MCP agent control your signed-in Chrome with full login state, offering normal browser tools and an optional Fast JEV mode for bounded-speed typed decisions on the same profile.

It gives AI agents a ranked, token-budgeted digest of what changed since their last cursor, with drill-down handles and cursor acknowledgement, read from a local database of file and SQL source changes. It enables agents to act on current business state without re-reading and diffing everything themselves.

An MCP server that lets an MCP client manage a self-hosted obot MCP gateway via its REST API.

Discover and evaluate APIs for AI agents with AN Score, then access them through MCP or REST with zero-signup discovery and managed execution paths.

An agent-native workflow MCP server that enables AI agents to execute text-defined, versionable workflows with checkpointing and state management.