Claude Context▌
by zilliztech
Claude Context offers semantic code search and indexing with vector embeddings and AST-based code splitting. Natural lan
Provides semantic code search and indexing using vector embeddings and AST-based code splitting, enabling natural language queries across codebases with automatic file filtering and support for multiple embedding providers and vector databases.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers working with large codebases
- / AI coding agents needing codebase context
- / Teams wanting cost-effective code search
- / Projects requiring semantic code understanding
capabilities
- / Search codebases using natural language queries
- / Index code using vector embeddings and AST parsing
- / Filter files automatically based on relevance
- / Connect to multiple embedding providers
- / Store embeddings in various vector databases
what it does
Adds semantic code search to Claude using vector embeddings, allowing natural language queries to find relevant code across large codebases without loading entire directories into context.
about
Claude Context is a community-built MCP server published by zilliztech that provides AI assistants with tools and capabilities via the Model Context Protocol. Claude Context offers semantic code search and indexing with vector embeddings and AST-based code splitting. Natural lan It is categorized under developer tools.
how to install
You can install Claude Context in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Claude Context is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme

Your entire codebase as Claude's context
<a href="https://discord.gg/mKc3R95yE5"><img height="20" src="https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white" alt="discord" /></a>
Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.
🧠 Your Entire Codebase as Context: Claude Context uses semantic search to find all relevant code from millions of lines. No multi-round discovery needed. It brings results straight into the Claude's context.
💰 Cost-Effective for Large Codebases: Instead of loading entire directories into Claude for every request, which can be very expensive, Claude Context efficiently stores your codebase in a vector database and only uses related code in context to keep your costs manageable.
🚀 Demo
Model Context Protocol (MCP) allows you to integrate Claude Context with your favorite AI coding assistants, e.g. Claude Code.
Quick Start
Prerequisites
<details> <summary>Get a free vector database on Zilliz Cloud 👈</summary>Claude Context needs a vector database. You can sign up on Zilliz Cloud to get an API key.

Copy your Personal Key to replace your-zilliz-cloud-api-key in the configuration examples.
You need an OpenAI API key for the embedding model. You can get one by signing up at OpenAI.
Your API key will look like this: it always starts with sk-.
Copy your key and use it in the configuration examples below as your-openai-api-key.
Configure MCP for Claude Code
System Requirements:
- Node.js >= 20.0.0 and < 24.0.0
Claude Context is not compatible with Node.js 24.0.0, you need downgrade it first if your node version is greater or equal to 24.
Configuration
Use the command line interface to add the Claude Context MCP server:
claude mcp add claude-context \
-e OPENAI_API_KEY=sk-your-openai-api-key \
-e MILVUS_TOKEN=your-zilliz-cloud-api-key \
-- npx @zilliz/claude-context-mcp@latest
See the Claude Code MCP documentation for more details about MCP server management.
Other MCP Client Configurations
<details> <summary><strong>OpenAI Codex CLI</strong></summary>Codex CLI uses TOML configuration files:
-
Create or edit the
~/.codex/config.tomlfile. -
Add the following configuration:
# IMPORTANT: the top-level key is `mcp_servers` rather than `mcpServers`.
[mcp_servers.claude-context]
command = "npx"
args = ["@zilliz/claude-context-mcp@latest"]
env = { "OPENAI_API_KEY" = "your-openai-api-key", "MILVUS_TOKEN" = "your-zilliz-cloud-api-key" }
# Optional: override the default 10s startup timeout
startup_timeout_ms = 20000
- Save the file and restart Codex CLI to apply the changes.
Gemini CLI requires manual configuration through a JSON file:
- Create or edit the
~/.gemini/settings.jsonfile. - Add the following configuration:
{
"mcpServers": {
"claude-context": {
"command": "npx",
"args": ["@zilliz/claude-context-mcp@latest"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"MILVUS_TOKEN": "your-zilliz-cloud-api-key"
}
}
}
}
- Save the file and restart Gemini CLI to apply the changes.
Create or edit the ~/.qwen/settings.json file and add the following configuration:
{
"mcpServers": {
"claude-context": {
"command": "npx",
"args": ["@zilliz/claude-context-mcp@latest"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
"MILVUS_TOKEN": "your-zilliz-cloud-api-key"
}
}
}
}
</details>
<details>
<summary><strong>Cursor</strong></summary>
<a href="https://cursor.com/install-mcp?name=claude-context&config=JTdCJTIyY29tbWFuZCUyMiUzQSUyMm5weCUyMC15JTIwJTQwemlsbGl6JTJGY29kZS1jb250ZXh0LW1jcCU0MGxhdGVzdCUyMiUyQyUyMmVudiUyMiUzQSU3QiUyMk9QRU5BSV9BUElfS0VZJTIyJTNBJTIyeW91ci1vcGVuYWktYXBpLWtleSUyMiUyQyUyMk1JTFZVU19BRERSRVNTJTIyJTNBJTIybG9jYWxob3N0JTNBMTk1MzAlMjIlN0QlN0Q%3D"><img src="https://cursor.com/deeplink/mcp-install-dark.svg" alt="Add claude-context MCP server to Cursor" height="32" /></a>
Go to: Settings -> Cursor Settings -> MCP -> Add new global MCP server
Pasting the following configuration into your Cursor ~/.cursor/mcp.json file is the recommended approach. You may also install in a specific project by creating .cursor/mcp.json in your project folder. See Cursor MCP docs for more info.
{
"mcpServers": {
"claude-context": {
"command": "npx",
"args": ["-y", "@zilliz/claude-context-mcp@latest"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
"MILVUS_TOKEN": "your-zilliz-cloud-api-key"
}
}
}
}
</details>
<details>
<summary><strong>Void</strong></summary>
Go to: Settings -> MCP -> Add MCP Server
Add the following configuration to your Void MCP settings:
{
"mcpServers": {
"code-context": {
"command": "npx",
"args": ["-y", "@zilliz/claude-context-mcp@latest"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
"MILVUS_TOKEN": "your-zilliz-cloud-api-key"
}
}
}
}
</details>
<details>
<summary><strong>Claude Desktop</strong></summary>
Add to your Claude Desktop configuration:
{
"mcpServers": {
"claude-context": {
"command": "npx",
"args": ["@zilliz/claude-context-mcp@latest"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
"MILVUS_TOKEN": "your-zilliz-cloud-api-key"
}
}
}
}
</details>
<details>
<summary><strong>Windsurf</strong></summary>
Windsurf supports MCP configuration through a JSON file. Add the following configuration to your Windsurf MCP settings:
{
"mcpServers": {
"claude-context": {
"command": "npx",
"args": ["-y", "@zilliz/claude-context-mcp@latest"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
"MILVUS_TOKEN": "your-zilliz-cloud-api-key"
}
}
}
}
</details>
<details>
<summary><strong>VS Code</strong></summary>
The Claude Context MCP server can be used with VS Code through MCP-compatible extensions. Add the following configuration to your VS Code MCP settings:
{
"mcpServers": {
"claude-context": {
"command": "npx",
"args": ["-y", "@zilliz/claude-context-mcp@latest"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
"MILVUS_TOKEN": "your-zilliz-cloud-api-key"
}
}
}
}
</details>
<details>
<summary><strong>Cherry Studio</strong></summary>
Cherry Studio allows for visual MCP server configuration through its settings interface. While it doesn't directly support manual JSON configuration, you can add a new server via the GUI:
- Navigate to Settings → MCP Servers → Add Server.
- Fill in the server details:
- Name:
claude-context - Type:
STDIO - Command:
npx - Arguments:
["@zilliz/claude-context-mcp@latest"] - Environment Variables:
OPENAI_API_KEY:your-openai-api-keyMILVUS_ADDRESS:your-zilliz-cloud-public-endpointMILVUS_TOKEN:your-zilliz-cloud-api-key
- Name:
- Save the configuration to activate the server.
Cline uses a JSON configuration file to manage MCP servers. To integrate the provided MCP server configuration:
-
Open Cline and click on the MCP Servers icon in the top navigation bar.
-
Select the Installed tab, then click Advanced MCP Settings.
-
In the `cline_mcp_setting
FAQ
- What is the Claude Context MCP server?
- Claude Context is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Claude Context?
- This profile displays 64 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★64 reviews- ★★★★★Shikha Mishra· Dec 28, 2024
Strong directory entry: Claude Context surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Hassan Sanchez· Dec 20, 2024
Claude Context has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Soo White· Dec 20, 2024
According to our notes, Claude Context benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Omar Anderson· Dec 8, 2024
Strong directory entry: Claude Context surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Diya Flores· Dec 4, 2024
Claude Context is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Noah Desai· Nov 27, 2024
Claude Context has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Diya Farah· Nov 23, 2024
Claude Context reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Yash Thakker· Nov 19, 2024
Claude Context has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Dev Okafor· Nov 11, 2024
Strong directory entry: Claude Context surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Omar Malhotra· Nov 11, 2024
I recommend Claude Context for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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