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AI coding assistants are amazing and powerful—until they start lying.
Like it just gets really frustrating when they hallucinate APIs or forget your project structure and break more than they fix.
And why does this happen?
Context.
They just don’t have enough context.
Context is everything for AI assistants. That’s why MCP is so important.
These MCP servers fix that. They ground your AI in the truth of your codebase—your files, libraries, memory, and decisions—so it stops guessing and starts delivering.
These five will change everything.
1. Context7 MCP Server
Context7 revolutionizes how AI models interact with library documentation—eliminating outdated references, hallucinated APIs, and unnecessary guesswork.
It sources up-to-date, version-specific docs and examples directly from upstream repositories — to ensure every answer reflects the exact environment you’re coding in.
Whether you’re building with React, managing rapidly evolving dependencies, or onboarding a new library, Context7 keeps your AI grounded in reality—not legacy docs.
It seamlessly integrates with tools like Cursor, VS Code, Claude, and Windsurf, and supports both manual and automatic invocation. With just a line in your prompt or an MCP rule, Context7 starts delivering live documentation, targeted to your exact project context.
Key features
On-the-fly documentation: Fetches exact docs and usage examples based on your installed library versions—no hallucinated syntax.
Seamless invocation: Auto-invokes via MCP client config or simple prompt cues like “use context7”.
Live from source: Pulls real-time content straight from upstream repositories and published docs.
Customizable resolution: Offers tools like
resolve-library-idandget-library-docsto fine-tune lookups.Wide compatibility: Works out-of-the-box with most major MCP clients across dozens of programming languages.
Errors it prevents
Calling deprecated or removed APIs
Using mismatched or outdated function signatures
Writing syntax that no longer applies to your version
Missing new required parameters or arguments
Failing to import updated module paths or packages
Powerful use cases
Projects built on fast-evolving frameworks like React, Angular, Next.js, etc.
Onboarding to unfamiliar libraries without constant tab switching
Working on teams where multiple versions of a library may be in use
Auditing legacy codebases for outdated API usage
Auto-generating code or tests with correct syntax and parameters for specific versions
Get Context7 MCP Server: LINK
2. Memory Bank MCP Server
The Memory Bank MCP server gives your AI assistant persistent memory across coding sessions and projects.
Instead of repeating the same explanations, code patterns, or architectural decisions, your AI retains context from past work—saving time and improving coherence. It’s built to work across multiple projects with strict isolation, type safety, and remote access, making it ideal for both solo and collaborative development.
Key features
Used by Execs at Google and OpenAI
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