Claude Context offers semantic code search and indexing with vector embeddings and AST-based code splitting. Natural lan
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
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
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
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
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Strong directory entry: Claude Context surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Claude Context has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Claude Context benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Strong directory entry: Claude Context surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Claude Context is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Claude Context has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Claude Context reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Claude Context has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Claude Context surfaces stars and publisher context so we could sanity-check maintenance before adopting.
I recommend Claude Context for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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Claude Desktop 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"
}
}
}
}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.
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.
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.

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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.
Model Context Protocol (MCP) allows you to integrate Claude Context with your favorite AI coding assistants, e.g. Claude Code.
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.
System Requirements:
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.
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.
Codex CLI uses TOML configuration files:
Create or edit the ~/.codex/config.toml file.
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
Gemini CLI requires manual configuration through a JSON file:
~/.gemini/settings.json file.{
"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"
}
}
}
}
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:
claude-contextSTDIOnpx["@zilliz/claude-context-mcp@latest"]OPENAI_API_KEY: your-openai-api-keyMILVUS_ADDRESS: your-zilliz-cloud-public-endpointMILVUS_TOKEN: your-zilliz-cloud-api-keyCline 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
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ 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.