Packages

mcp-name: io.modelcontextprotocol.anonymous/weather-server-python

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The wiki-mcp-server package is an MCP (Model Context Protocol) server that exposes wiki content and/or wiki-related operations to AI agents via MCP tools. This lets an agent query and retrieve wiki information as part of its context during reasoning and task completion.

[](https://archestra.ai/mcp-catalog/wooonster__hocr_mcp_server)

A learning-oriented MCP (Model Context Protocol) server implemented in Java. It communicates over stdio using JSON-RPC 2.0, supports the MCP initialize handshake, lists tools via tools/list, and executes a basic tool via tools/call (with an echo example).

DBC-MCP-Server is a Spring Boot service that exposes a Model Context Protocol (MCP) interface for database connection management and AI-assisted database metadata querying. It supports multiple SQL databases (e.g., MySQL, PostgreSQL, SQL Server, SQLite) via dynamic datasource switching and provides MCP “tool functions” for schema/introspection (tables, columns, foreign keys, indexes, engine) plus SQL execution and row count/statistics.

Digma is an MCP server that integrates code observability and dynamic code analysis from Digma.ai into AI agents. It enables agents to access runtime insights, performance data, and code issues discovered through distributed tracing and pre-production observability.

iconserver is an image/icon proxy service that serves icon assets (e.g., from an upstream source or local resources) via HTTP, typically transforming/caching requests so clients can fetch consistent icon URLs.

Provides a demo Java MCP (Model Context Protocol) server that exposes tools over an SSE-based HTTP transport (Jetty). The repository also demonstrates a “fast-agent” workflow that can call other MCP servers (e.g., websearch for geocoding) and then call the included weather MCP server to summarize forecasts.

Provides a locally hosted, read-only MCP server that wraps the CData JDBC Driver for Microsoft Exchange. It exposes Exchange data as relational SQL tables via MCP tools (get_tables, get_columns, run_query) using stdio for client communication (e.g., Claude Desktop).

Provides an MCP server that reads local PDF files from a directory specified at startup, exposing tools (e.g., list/search PDFs and read PDF contents) to an MCP-capable client.

Provides an MCP server (Streamable HTTP) that runs Python code in a fresh interpreter state with pyautogui instrumentation, returning captured stdout/stderr/results and inline screenshots (including mouse-operation previews). Includes a macOS-only helper to keep the display awake before automation.

Python-based voice AI client ported from xiaozhi-esp32, providing a full AI voice assistant experience with smart home IoT integration, multimodal capabilities, and MCP tool support — without requiring specialized hardware.

quick-data-mcp is an MCP server (Python) intended to let an AI agent perform agentic analytics on user-provided .json and .csv files via MCP Tools/Resources/Prompts, configured through an .mcp.json file pointing at a local directory.

airbyte-api-server is an Airbyte component that exposes an API surface for interacting with Airbyte (commonly used to control/run syncs and manage operations). It typically serves as the API layer behind Airbyte’s server/worker stack rather than being a standalone data connector service.

ASK (Agent Skills Kit) is a Go-based CLI (and optional web/desktop UI) for managing “agent skills” from multiple sources. It installs/uninstalls skills, syncs them across multiple agent products (e.g., Claude, Cursor, Codex, Copilot, Windsurf, Gemini CLI, OpenClaw), supports version locking via an ask.lock file, and provides a security scanning/audit workflow plus offline/private-repo support.

Incipit is a Go-based CLI that takes structured resume data (JSON/Markdown) and generates formatted outputs (PDF via HTML/Chromium and/or LaTeX, DOCX, and Markdown), using a template system. It also provides AI commands to create/review/optimize resumes via multiple LLM providers (Anthropic, OpenAI, Google, or local Ollama), and can validate inputs using an exported JSON Schema.

An MCP server for integrating with Azure DevOps, exposing tools that let an agent interact with Azure DevOps resources (e.g., projects, work items, pipelines/releases) via the Model Context Protocol.

MCP server that exposes Prisma/ORM operations to an MCP-capable AI agent, enabling the agent to inspect schema and perform database actions through Prisma tooling.

A MCP (Model Context Protocol) server package named "patersr-strands-mcp-server". From the name alone, it is intended to expose a set of MCP tools/actions to an AI agent, likely related to the "Patersr" and "Strands" domains/resources.