"Integration guide for Segment.io analytics platform" matching MCP servers:

Integration project for Model Context Protocol (MCP) servers with Claude Desktop App, enabling filesystem operations, development support, and file management through natural language.

Enables AI tools to understand a database, inspect schema, and run safe SELECT queries with SQL guardrails, plus optional codebase reading.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

An MCP server that exposes macOS Spotlight search as tools, wrapping mdfind and mdls to provide full-text and metadata file search across the system.

Enables comprehensive filesystem operations across Linux, macOS, and Windows with platform-aware command execution, secure path restrictions, and intelligent adaptations for file search, directory management, and shell commands specific to each operating system.

Enables AI agents to remotely operate visual design tools via MCP protocol, with composable architecture for image processing, file operations, and workflow automation.

A collection of small MCP servers for macOS automation that expose Apple Mail, MoneyMoney, and Spotlight functionality as tools via AppleScript and command-line, enabling AI applications to search mail, manage contacts and transactions, and perform system-wide file searches through natural language.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

MCP server that encapsulates Apple Mail on macOS via AppleScript, enabling invoice PDF search, attachment saving, and message flagging through natural language.

Provides a complete end-to-end MCP server implementation with file system tools, web scraping capabilities, and system information access. Includes ready-to-use configuration files and integration examples for Claude Desktop, ChatGPT, and other AI models.

Self-hosted MCP coding server and unified local Control Center for ChatGPT web, enabling file editing, command execution, Git operations, and optional upstream MCP tools with conversation access controls.

Enables users to safely read, write, edit, create directories, and list trees within a structured local Windows environment, with strict path validation and Git-based undo/version control.

MCP server for Obsidian vaults, optimised for Cursor agents — safe note editing, lean tool surface, direct filesystem access.

A server implementation that enables LLMs to programmatically manage tasks in Todo.txt files using the Model Context Protocol (MCP), supporting operations like adding, completing, deleting, listing, searching, and filtering tasks.

Lets any MCP-compatible AI assistant read and edit Autodesk Civil 3D drawings through tools for alignments, surfaces, corridors, pipe networks, quantity takeoff, and cut/fill, using a local bridge plugin and named pipes.

Enables AI agents to interact with a sandboxed filesystem via MCP tools for reading, writing, searching, and monitoring files, including batch processing and resource discovery for resume management.

A FastAPI-based JSON-RPC 2.0 server implementation that enables users to work with HDF5 files, submit Slurm jobs, retrieve CPU information, and visualize CSV data through standardized API endpoints.

Enables agents to read, search, batch process, and watch directories of resume files via JSON-RPC MCP methods and resource discovery.

Enables MCP clients to interact with a filesystem by listing, reading, writing, and monitoring files, as well as extracting resume text and batch processing files.

Enables file system operations (read, write, list, search, watch, batch process) via MCP over JSON-RPC 2.0, used by a resume matching agent.