12 MCP Servers You Can Use in 2025
Author(s): Kalash Vasaniya
Originally published on Towards AI.
Bridging LLMs to Data, Tools, and Services
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MCP (Model Context Protocol) is rapidly becoming the de facto standard for connecting large language models (LLMs) to the rich ecosystem of data, tools, and services they need to be truly useful. Instead of hard‑coding API calls into every prompt or crafting elaborate “scratchpads,” MCP servers expose a uniform interface that lets your LLM dynamically discover capabilities, negotiate parameters, and execute actions, all while maintaining safety, auditability, and context continuity.
What it does: It provides your model with read/write/create rights on a sandbox file system so it can ingest local dumps, output reports, or template out new project structures.
Sandbox enforcement limits the model to access only certain folders.File-type filters (i.e., permit .csv and .md but exclude executables).Directory monitoring for real-time information.Processing multiple logs or data exports simultaneously.Auto-generating starter code templates.Automated document assembly processes.Not suitable for very sensitive information unless you include additional encryption.If large file systems are not designed well, there can be delays.
What it does: Connects your LLM to GitHub repositories — providing browser, searching, diff-based updates, pull request generation, and merging.
Searching code using natural language queries.PR writing, such as different previews.Multi-repo orchestration… Read the full blog for free on Medium.
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