12 MCP Servers You Can Use in 2025 12 MCP Servers You Can Use in 2025 0 like May 19, 2025 Share this post Author: Kalash Vasaniya Originally published on Towards AI. Bridging LLMs to Data, Tools, and ServicesSource: From AI-Generated If..."> 12 MCP Servers You Can Use in 2025 12 MCP Servers You Can Use in 2025 0 like May 19, 2025 Share this post Author: Kalash Vasaniya Originally published on Towards AI. Bridging LLMs to Data, Tools, and ServicesSource: From AI-Generated If..." /> 12 MCP Servers You Can Use in 2025 12 MCP Servers You Can Use in 2025 0 like May 19, 2025 Share this post Author: Kalash Vasaniya Originally published on Towards AI. Bridging LLMs to Data, Tools, and ServicesSource: From AI-Generated If..." />
12 MCP Servers You Can Use in 2025

12 MCP Servers You Can Use in 2025

0 like

May 19, 2025

Share this post

Author: Kalash Vasaniya

Originally published on Towards AI.

Bridging LLMs to Data, Tools, and ServicesSource: From AI-Generated
If you’re not a member but want to read this article, see this friend link here.
MCPis rapidly becoming the de facto standard for connecting large language modelsto 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.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.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Towards AI - Medium

Share this post
#mcp #servers #you #can #use
12 MCP Servers You Can Use in 2025
12 MCP Servers You Can Use in 2025 0 like May 19, 2025 Share this post Author: Kalash Vasaniya Originally published on Towards AI. Bridging LLMs to Data, Tools, and ServicesSource: From AI-Generated If you’re not a member but want to read this article, see this friend link here. MCPis rapidly becoming the de facto standard for connecting large language modelsto 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.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. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI Towards AI - Medium Share this post #mcp #servers #you #can #use
TOWARDSAI.NET
12 MCP Servers You Can Use in 2025
12 MCP Servers You Can Use in 2025 0 like May 19, 2025 Share this post Author(s): Kalash Vasaniya Originally published on Towards AI. Bridging LLMs to Data, Tools, and ServicesSource: From AI-Generated If you’re not a member but want to read this article, see this friend link here. 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. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI Towards AI - Medium Share this post
0 Σχόλια 0 Μοιράστηκε