An official Qdrant Model Context Protocol (MCP) server implementation

Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.

Exposes JSON-RPC 2.0 tools that let AI agents scan Base L2 lending positions approaching liquidation, simulate flash-loan-backed debt rescue plans, and generate the calldata needed to repay Morpho Blue and Aave v3 debt while avoiding the 5% penalty. Agents and builders can also attach a referral wallet to collect an instant 0.05% USDC revenue share paid atomically in the same block.

Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.

Enables Claude Code users to inventory the MCP servers, skills, commands, agents and plugins installed on their machine, estimate how many tokens each one adds to every request, and switch them off per project or globally, including across other AI coding tools. It also monitors live sessions to report real token usage and the savings achieved from disabled items.

A stdio MCP server that lets AI coding tools on a Mac speak text aloud through the local Speaklna text-to-speech app. It exposes four tools (speak, stop, status, voices) so agents can voice replies, halt playback, check state, and list available voices, but cannot import voices or change settings.

Drives the local Doubao desktop client through its DevTools interface, letting an agent read and send chats, run task-mode work, hand off a project directory and take it back, and call Doubao-only capabilities like image generation and step traces. Also borrows Doubao's built-in skill set for cross-checking and project handoff, with a UI badge showing which side currently owns the work.

Enables Claude Code to delegate tasks to persistent GitHub Copilot CLI sessions via MCP, inspect pending tool requests, and approve each operation once or deny it while continuing multi-turn context. It bridges ACP runtime sessions locally over stdio without a public service or background daemon.

Lets AI coding agents build, test, and lint Android projects with Gradle, control devices and emulators via adb, automate UI through screenshots and input injection, and use a live IDE bridge for refactoring, code inspection, and run configurations. Works with any MCP client over stdio or authenticated HTTP.

A local stdio MCP server that enables coding agents to find licensed photos and icons, generate color palettes and simple SVG assets, and preview static web prototypes. It also supports editable agent skills for design and prototype review workflows.

This MCP server lets an agent run local binary inspection on ELF, Mach-O, PE, APK, IPA, ASAR, WebAssembly, and firmware targets — pulling symbols, sections, classified strings, disassembly, and mitigation posture, and flagging dangerous imports and CWE patterns. It exposes eight stdio JSON-RPC tools (with no external API keys) that feed a multi-agent swarm for attack-surface mapping and exploit-chain synthesis.

Provides a shared, repo-local memory that lets coding agents recall relevant decisions, conventions, gotchas, and open threads, save new entries, coordinate file claims, and cache file summaries across tools and sessions.

Enables AI agents to place and verify provably fair dice bets, manage shared bankroll vault liquidity positions, inspect incentives and positions, and read or send verified chat messages over HTTP or Stdio, including website-independent on-chain memo workflows.

Enables MCP hosts to spawn, supervise, and collect results from parallel panels of pinned-model OpenCode v2 agents for delegated tasks, reviews, and cross-model comparisons. Supports per-member roles, models, permissions, follow-up prompts, cancellation, and persisted result retrieval.

Enables AI agents to debug Commodore software in a locally running VICE emulator through its text remote monitor, inspecting registers, memory and screens, disassembling code, setting breakpoints and watchpoints, controlling execution, and working with disk images, snapshots and exported graphics. Runs locally over stdio and includes safety guidance for state-changing operations.

Enables AI agents to discover and work with a user's permitted Excalidraw boards through a single MCP endpoint, reading and adding elements, images, and snapshots while respecting owner, view, edit, and guest-link access controls.

Embeds a runtime MCP inspector in a NestJS app so coding agents can inspect the module and provider graph, routes and their guards/interceptors/pipes/filters, logs, request traces, event listeners, and scheduled jobs through an HTTP endpoint.

Enables AI coding agents to query locally installed language servers over stdio MCP for read-only code intelligence, including definitions, references, implementations, hover types, symbols, and diagnostics.

Enables AI agents to build, validate, and submit ledger-native XRPL transactions against public nodes — escrows, XRP and token payments, DEX/AMM swaps and liquidity, issuer clawback, and x402 pay-per-request — with validated-ledger proof of results. State-changing calls go to the account owner for browser signing, while an owner-funded agent account allows autonomous spending bounded by on-ledger balance and local policy limits.

Enables coding agents to navigate and verify a contract-backed semantic graph of TypeScript backends, inspect change impact, run checks, explain failures, and draft human-reviewable contracts through bounded MCP tools and matching JSON CLI output.

Keeps large tool outputs out of an agent's context window by spilling them to disk and handing back a short pointer instead. Lets the agent pull only what it needs — exact numbered line ranges read directly from disk, or verbatim relevant lines returned by a small model answering a question about the stored output, plus tools to open, list, and close documents.

Enables AI agents to read a user's SRCE Moodle account data, including grades, deadlines, calendar events, course files, forum posts, and messages, with optional private-message sending gated by phone approval. It can run as a Cloudflare Worker or self-hosted via Node or Docker.

Enables two AI agents to share a persistent task mailbox over remote MCP, so one can leave work, the other can claim and complete it, and results are written back with optional webhook wake-ups.

Frontier model solution tracing, then made the prompting skills so Sonnet, GPT, DeepSeek, GLM, Kimi, ETC models work like that