Packages

MCP server that integrates with Linear's issue tracking system, allowing LLMs to create, update, search, and comment on Linear issues through standardized MCP tools and resources.

Markplane is a local, markdown-first project management tool for organizing epics, tasks, plans, and notes inside a repository (e.g., .markplane/). It generates a token-efficient .context/ directory for AI assistants and includes a built-in MCP server (JSON-RPC over stdio) plus a local web UI to manage and visualize project state.

mcp-jest is a Jest-like testing framework/runner for Model Context Protocol (MCP) servers. It provides a CLI and library API to run automated protocol/tool/resource/prompt tests (including snapshot testing) against MCP servers over supported transports (stdio by default; HTTP streaming; SSE) and can validate MCP compliance and generate reports/CI-friendly outputs.

Provides an MCP server that lets an AI assistant interact with your LogSeq knowledge base via LogSeq's local HTTP API. It supports reading, creating, updating, deleting pages/blocks, searching pages/content, executing Logseq DSL queries, and (optionally) semantic vector search and DB-mode property operations.

[](https://github.com/abhi1693/openclaw-mission-control/actions/workflows/ci.yml) 

Exports and archives Slack messages, threads, files, and user data locally without requiring admin privileges. Includes an MCP server for AI agent integration with archived data.

thermal-mcp-server is a Python-based MCP server exposing a physics/engineering model for liquid-cooled GPU thermal behavior. It estimates junction temperatures and hydraulic pressure drops, and can search for minimum coolant flow rates for a target junction temperature and compute rack-level thermal requirements for uniform GPU assumptions.

Provides a Model Context Protocol (MCP) server that exposes VMware ESXi hypervisor management capabilities as MCP tools, including host operations, VM lifecycle actions, storage/network management, and resource monitoring.

MCPStore is a Python orchestration layer that manages MCP service lifecycles and adapts them for use with popular AI agent frameworks like LangChain, LangGraph, AutoGen, CrewAI, and LlamaIndex through a unified API.

Provides two ways to run MCP (Model Context Protocol) servers that expose ACI.dev managed functions/tools to MCP clients: an apps-specific server that exposes tools from selected apps, and a unified server that can discover and execute tools across all available functions (via meta-tools).

An MCP server (Node.js) that lets MCP clients execute SQL against multiple database types via an apiSQL API gateway, with support for runtime switching between configured data sources (DS/SUDB), and both DDL/DML plus stored procedures/UDFs. It can run over MCP stdio by default and also offers a streamable HTTP transport mode.

Provides an MCP server that lets AI assistants query Azure retail pricing, compare prices across regions/SKUs, estimate usage-based costs, and perform FinOps-oriented analyses (RI break-even, region recommendations, spot intelligence, and orphaned resource cost estimation).

Dropbox MCP server (Go) that exposes Dropbox functionality (auth, file/folder operations, sharing, and revision history/restore) to AI assistants via the Model Context Protocol. Supports OAuth2 and large-file chunked uploads (per README).

Horizon is a self-hosted (Python) AI-powered tech news aggregator that fetches items from multiple sources, deduplicates them, uses an LLM to score/filter items, enriches them with background web search, and generates bilingual (English/Chinese) daily markdown briefings that can be deployed to GitHub Pages; it also includes an MCP server so agents can drive the pipeline programmatically and an optional self-hosted email subscription flow (SMTP/IMAP).

mcp-wireshark is a Python-based MCP server that exposes Wireshark/tshark functionality to MCP-compatible AI clients. It can run live packet capture, read/analyze .pcap/.pcapng files, apply display filters, follow TCP/UDP streams, and export analysis results (e.g., JSON) via defined MCP tools.

An adapter extension for the Pi coding agent that proxies and manages MCP (Model Context Protocol) servers. It offers a single lightweight proxy tool for tool search/describe/calls, supports lazy/eager/keep-alive server lifecycles with cached tool metadata, optional promotion of specific MCP tools into Pi’s direct tool list, and MCP UI support with bidirectional messaging.

A skill/plugin that turns an AI coding/planning agent workflow into a persistent, file-based system (Manus-style). It creates and maintains markdown planning/progress files (e.g., task_plan.md, findings.md, progress.md) and uses IDE/agent hooks to re-read the plan before actions, remind progress updates after tool use, log errors, and verify completion before stopping.

validation-mcp-server is an offline, Python-based Model Context Protocol (MCP) server that provides Ethereum address/key validation and related cryptographic utilities (e.g., EIP-55 checksum validation, private-key range checking, checksummed conversion, signature component/value validation, hashing like keccak256, function selector encoding/decoding, ENS format validation, and storage-slot computation).

Provides a Model Context Protocol (MCP) server exposing Wikidata exploration/query tools (item/property search, entity statements/values, hierarchy retrieval, and SPARQL execution). A hosted endpoint and local/Docker run instructions are provided.

Provides an MCP server (Python) exposing tools to parse, validate, extract, and manipulate XLIFF and TMX localization files, including tag-preserving processing, replacement of XLIFF targets from translated content, and CSV/JSON exports. Also ships a skills/catalog workflow layer intended for agent-guided localization tasks.