"Information about Jira Integration" 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.

Fetches Jira attachments and returns them inline (for small images) or as local paths for larger files and other types, enabling AI models to access Jira attachments directly.

Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.

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.

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.

Provides file system access for resume matching through JSON-RPC, enabling semantic search and workflow orchestration with LangGraph.

An MCP server exposing calculator, file read, and file write tools for the Gemini CLI agent, enabling mathematical computations and file operations through natural language.

Provides filesystem access and integration with Z.ai's GLM-4 models for code generation and reasoning tasks. Designed to work as a git submodule with automatic parent repository detection.

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.

Enables reading, normalizing, validating, merging, and exporting data from Excel, CSV, JSON, and SQLite sources into a unified schema, with tools exposed via FastMCP.

Provides MCP tools for reading, listing, writing, searching, watching, and batch-processing files, enabling automated file management and resume matching workflows.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent framework to 100+ accounting systems, HRIS platforms, file storage providers, and more through one integration. More information https://www.apideck.com/mcp-server

A modular Python MCP server providing tools for text echoing, system information, time queries, arithmetic, file reading, and more, designed for seamless integration with Cline and other MCP clients.

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.

A comprehensive MCP server with 30+ custom tools organized into categories: date/time operations, file management, system information, text processing, and web operations. Enables async communication with robust error handling and flexible CLI integration.

Enables Claude to read and analyze project schedule files in OmniPlan (.oplx) and Microsoft Project (.mpp) formats, answering questions about tasks, milestones, resources, and progress.

Provides advanced document search and processing capabilities through vector stores, including PDF processing, semantic search, web search integration, and file operations. Enables users to create searchable document collections and retrieve relevant information using natural language queries.