Move VSCode docs below Claude Code (#46)
It's done to keep the order of how the tools were added.
This commit is contained in:
Kacper Łukawski
194
README.md
194
README.md
@@ -157,6 +157,103 @@ This MCP server can be used with any MCP-compatible client. For example, you can
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[Cursor](https://docs.cursor.com/context/model-context-protocol) and [VS Code](https://code.visualstudio.com/docs), which provide built-in support for the Model Context
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Protocol.
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### Using with Cursor/Windsurf
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You can configure this MCP server to work as a code search tool for Cursor or Windsurf by customizing the tool
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descriptions:
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```bash
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QDRANT_URL="http://localhost:6333" \
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COLLECTION_NAME="code-snippets" \
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TOOL_STORE_DESCRIPTION="Store reusable code snippets for later retrieval. \
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The 'information' parameter should contain a natural language description of what the code does, \
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while the actual code should be included in the 'metadata' parameter as a 'code' property. \
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The value of 'metadata' is a Python dictionary with strings as keys. \
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Use this whenever you generate some code snippet." \
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TOOL_FIND_DESCRIPTION="Search for relevant code snippets based on natural language descriptions. \
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The 'query' parameter should describe what you're looking for, \
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and the tool will return the most relevant code snippets. \
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Use this when you need to find existing code snippets for reuse or reference." \
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uvx mcp-server-qdrant --transport sse # Enable SSE transport
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```
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In Cursor/Windsurf, you can then configure the MCP server in your settings by pointing to this running server using
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SSE transport protocol. The description on how to add an MCP server to Cursor can be found in the [Cursor
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documentation](https://docs.cursor.com/context/model-context-protocol#adding-an-mcp-server-to-cursor). If you are
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running Cursor/Windsurf locally, you can use the following URL:
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```
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http://localhost:8000/sse
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```
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> [!TIP]
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> We suggest SSE transport as a preferred way to connect Cursor/Windsurf to the MCP server, as it can support remote
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> connections. That makes it easy to share the server with your team or use it in a cloud environment.
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This configuration transforms the Qdrant MCP server into a specialized code search tool that can:
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1. Store code snippets, documentation, and implementation details
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2. Retrieve relevant code examples based on semantic search
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3. Help developers find specific implementations or usage patterns
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You can populate the database by storing natural language descriptions of code snippets (in the `information` parameter)
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along with the actual code (in the `metadata.code` property), and then search for them using natural language queries
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that describe what you're looking for.
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> [!NOTE]
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> The tool descriptions provided above are examples and may need to be customized for your specific use case. Consider
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> adjusting the descriptions to better match your team's workflow and the specific types of code snippets you want to
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> store and retrieve.
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**If you have successfully installed the `mcp-server-qdrant`, but still can't get it to work with Cursor, please
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consider creating the [Cursor rules](https://docs.cursor.com/context/rules-for-ai) so the MCP tools are always used when
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the agent produces a new code snippet.** You can restrict the rules to only work for certain file types, to avoid using
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the MCP server for the documentation or other types of content.
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### Using with Claude Code
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You can enhance Claude Code's capabilities by connecting it to this MCP server, enabling semantic search over your
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existing codebase.
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#### Setting up mcp-server-qdrant
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1. Add the MCP server to Claude Code:
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```shell
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# Add mcp-server-qdrant configured for code search
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claude mcp add code-search \
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-e QDRANT_URL="http://localhost:6333" \
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-e COLLECTION_NAME="code-repository" \
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-e EMBEDDING_MODEL="sentence-transformers/all-MiniLM-L6-v2" \
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-e TOOL_STORE_DESCRIPTION="Store code snippets with descriptions. The 'information' parameter should contain a natural language description of what the code does, while the actual code should be included in the 'metadata' parameter as a 'code' property." \
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-e TOOL_FIND_DESCRIPTION="Search for relevant code snippets using natural language. The 'query' parameter should describe the functionality you're looking for." \
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-- uvx mcp-server-qdrant
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```
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2. Verify the server was added:
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```shell
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claude mcp list
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```
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#### Using Semantic Code Search in Claude Code
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Tool descriptions, specified in `TOOL_STORE_DESCRIPTION` and `TOOL_FIND_DESCRIPTION`, guide Claude Code on how to use
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the MCP server. The ones provided above are examples and may need to be customized for your specific use case. However,
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Claude Code should be already able to:
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1. Use the `qdrant-store` tool to store code snippets with descriptions.
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2. Use the `qdrant-find` tool to search for relevant code snippets using natural language.
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### Run MCP server in Development Mode
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The MCP server can be run in development mode using the `mcp dev` command. This will start the server and open the MCP
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inspector in your browser.
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```shell
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COLLECTION_NAME=mcp-dev mcp dev src/mcp_server_qdrant/server.py
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```
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### Using with VS Code
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For one-click installation, click one of the install buttons below:
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@@ -333,103 +430,6 @@ For workspace configuration with Docker, use this in `.vscode/mcp.json`:
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}
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```
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### Using with Cursor/Windsurf
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You can configure this MCP server to work as a code search tool for Cursor or Windsurf by customizing the tool
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descriptions:
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```bash
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QDRANT_URL="http://localhost:6333" \
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COLLECTION_NAME="code-snippets" \
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TOOL_STORE_DESCRIPTION="Store reusable code snippets for later retrieval. \
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The 'information' parameter should contain a natural language description of what the code does, \
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while the actual code should be included in the 'metadata' parameter as a 'code' property. \
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The value of 'metadata' is a Python dictionary with strings as keys. \
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Use this whenever you generate some code snippet." \
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TOOL_FIND_DESCRIPTION="Search for relevant code snippets based on natural language descriptions. \
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The 'query' parameter should describe what you're looking for, \
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and the tool will return the most relevant code snippets. \
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Use this when you need to find existing code snippets for reuse or reference." \
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uvx mcp-server-qdrant --transport sse # Enable SSE transport
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```
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In Cursor/Windsurf, you can then configure the MCP server in your settings by pointing to this running server using
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SSE transport protocol. The description on how to add an MCP server to Cursor can be found in the [Cursor
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documentation](https://docs.cursor.com/context/model-context-protocol#adding-an-mcp-server-to-cursor). If you are
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running Cursor/Windsurf locally, you can use the following URL:
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```
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http://localhost:8000/sse
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```
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> [!TIP]
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> We suggest SSE transport as a preferred way to connect Cursor/Windsurf to the MCP server, as it can support remote
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> connections. That makes it easy to share the server with your team or use it in a cloud environment.
|
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This configuration transforms the Qdrant MCP server into a specialized code search tool that can:
|
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|
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1. Store code snippets, documentation, and implementation details
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2. Retrieve relevant code examples based on semantic search
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3. Help developers find specific implementations or usage patterns
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You can populate the database by storing natural language descriptions of code snippets (in the `information` parameter)
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along with the actual code (in the `metadata.code` property), and then search for them using natural language queries
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that describe what you're looking for.
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> [!NOTE]
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> The tool descriptions provided above are examples and may need to be customized for your specific use case. Consider
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> adjusting the descriptions to better match your team's workflow and the specific types of code snippets you want to
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> store and retrieve.
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**If you have successfully installed the `mcp-server-qdrant`, but still can't get it to work with Cursor, please
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consider creating the [Cursor rules](https://docs.cursor.com/context/rules-for-ai) so the MCP tools are always used when
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the agent produces a new code snippet.** You can restrict the rules to only work for certain file types, to avoid using
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the MCP server for the documentation or other types of content.
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### Using with Claude Code
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You can enhance Claude Code's capabilities by connecting it to this MCP server, enabling semantic search over your
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existing codebase.
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#### Setting up mcp-server-qdrant
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1. Add the MCP server to Claude Code:
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```shell
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# Add mcp-server-qdrant configured for code search
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claude mcp add code-search \
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-e QDRANT_URL="http://localhost:6333" \
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-e COLLECTION_NAME="code-repository" \
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-e EMBEDDING_MODEL="sentence-transformers/all-MiniLM-L6-v2" \
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-e TOOL_STORE_DESCRIPTION="Store code snippets with descriptions. The 'information' parameter should contain a natural language description of what the code does, while the actual code should be included in the 'metadata' parameter as a 'code' property." \
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-e TOOL_FIND_DESCRIPTION="Search for relevant code snippets using natural language. The 'query' parameter should describe the functionality you're looking for." \
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-- uvx mcp-server-qdrant
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```
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2. Verify the server was added:
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```shell
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claude mcp list
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```
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#### Using Semantic Code Search in Claude Code
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Tool descriptions, specified in `TOOL_STORE_DESCRIPTION` and `TOOL_FIND_DESCRIPTION`, guide Claude Code on how to use
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the MCP server. The ones provided above are examples and may need to be customized for your specific use case. However,
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Claude Code should be already able to:
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1. Use the `qdrant-store` tool to store code snippets with descriptions.
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2. Use the `qdrant-find` tool to search for relevant code snippets using natural language.
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### Run MCP server in Development Mode
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The MCP server can be run in development mode using the `mcp dev` command. This will start the server and open the MCP
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inspector in your browser.
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```shell
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COLLECTION_NAME=mcp-dev mcp dev src/mcp_server_qdrant/server.py
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```
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## Contributing
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If you have suggestions for how mcp-server-qdrant could be improved, or want to report a bug, open an issue!
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