Six Open Source MCP Tools Every Developer Should Know

- The 6 High-Efficiency Open-Source MCP Servers Handpicked by Avi Chawla After Testing Over 100 MCP Servers in Two Months - Tools to Assist AI Agents with Code Execution, Web Crawling, Memory Retention, GitHub, and Database Queries [Unblock Media] — May 28, 2025 Model Context Protocol(MCP) are rapidly evolving, redefining the way agentic AI interfaces with external data, tools, and environments. Avi Chawla, a developer and AI infrastructure researcher, recently tested over 100 MCP servers over the past few months and shared his recommendations for six open-source MCP servers. Here are the six selected servers and the benefits they offer to developers: 1. Bright Data MCP Server This server provides seamless web access with over 30 tools for browsing, crawling, and interacting while avoiding bot defenses. Unlike traditional scrapers, it selects the optimal tool for each website's structure, making it ideal for real-time data pipelines, SEO analysis, and competitor research. 2. Graphiti MCP Server Agents typically "forget" context after each task. Graphiti builds a time-aware knowledge graph to provide persistent and time-sensitive memory, enabling agents that learn and evolve in customer service, regression analysis pipelines (RAG), or internal search systems. 3. GitIngest MCP Server GitIngest is ideal for exploring codebases, allowing agents to interface directly with GitHub repositories. With its two core tools, `git_directory_structure` and `git_read_important_files`, agents can understand and logically approach unfamiliar codebases without complete indexing. 4. Terminal MCP Server This server provides Claude or other agents with full shell access, including file I/O and command execution. It enables secure local operations, such as reading logs, managing files, or running internal scripts, making it useful for DevOps, testing, or agent-based RPA (Robotic Process Automation) use cases. 5. Code Executor MCP Server Need to execute dynamic Python code in a controlled environment? This server allows agents to run Python in a pre-defined Conda environment, ensuring compatibility and reproducibility, which is crucial for agents handling data science, model inference, or logic-centric automation. 6. MindsDB MCP Server Designed for data integration, this MCP connects various databases and platforms into a single query layer. It allows agents to query structured data across systems like MySQL, MongoDB, or Google Sheets, making it ideal for cross-platform analysis and LLM (Large Language Model)-based dashboards. What it means for developers MCPs are essential for developers looking to build modular, multi-agent systems or enhance the functionality of a single LLM. By decoupling tools from model weights and fine-tuning, MCP servers open up the possibility of plug-and-play intelligence, representing a critical step toward more autonomous and interpretable AI. Avi Chawla tweeted, "We are in the infrastructure phase of AI agent evolution. These servers are like the middleware of intelligent workflows." With MCP architectures like LangGraph, Autogen, and CrewAI gaining attention, these six tools represent the cutting edge of agent tools in 2025.