Astra DB
เซิร์ฟเวอร์สำหรับโต้ตอบกับฐานข้อมูลแบบบริการ (Database-as-a-Service) ของ Astra DB ที่สร้างบน Apache Cassandra
เอกสาร
Astra DB MCP Server
A Model Context Protocol (MCP) server for interacting with Astra DB. MCP extends the capabilities of Large Language Models (LLMs) by allowing them to interact with external systems as agents.
Prerequisites
You need to have a running Astra DB database. If you don't have one, you can create a free database here. From there, you can get two things you need:
- An Astra DB Application Token
- The Astra DB API Endpoint
To learn how to get these, please read the getting started docs.
Adding to an MCP client
Here's how you can add this server to your MCP client.
IBM Bob
For IBM Bob IDE, follow the procedure at this documentation.

For IBM Bob Shell, follow the procedure at this documentation.
Claude Desktop

To add this to Claude Desktop, go to Preferences -> Developer -> Edit Config and add this JSON blob to claude_desktop_config.json:
{
"mcpServers": {
"astra-db-mcp": {
"command": "npx",
"args": ["-y", "@datastax/astra-db-mcp"],
"env": {
"ASTRA_DB_APPLICATION_TOKEN": "your_astra_db_token",
"ASTRA_DB_API_ENDPOINT": "your_astra_db_endpoint"
}
}
}
}
Optional Keyspace Configuration:
By default, this server uses the keyspace configured in the underlying Astra DB library (typically default_keyspace). If you need to connect to a specific keyspace, you can add the ASTRA_DB_KEYSPACE variable to the env object above, like so:
"env": {
"ASTRA_DB_APPLICATION_TOKEN": "your_astra_db_token",
"ASTRA_DB_API_ENDPOINT": "your_astra_db_endpoint",
"ASTRA_DB_KEYSPACE": "your_desired_keyspace"
}
Windows PowerShell Users:
npx is a batch command so modify the JSON as follows:
"command": "cmd",
"args": ["/k", "npx", "-y", "@datastax/astra-db-mcp"],
Cursor

To add this to Cursor, go to Settings -> Cursor Settings -> MCP
From there, you can add the server by clicking the "+ Add New MCP Server" button, where you should be brought to an mcp.json file.
Tip: there is a
~/.cursor/mcp.jsonthat represents your Global MCP settings, and a project-specific.cursor/mcp.jsonfile that is specific to the project. You probably want to install this MCP server into the project-specific file.
Add the same JSON as indiciated in the Claude Desktop instructions.
Alternatively you may be presented with a wizard, where you can enter the following values (for Unix-based systems):
- Name: Whatever you want
- Type: Command
- Command:
env ASTRA_DB_APPLICATION_TOKEN=your_astra_db_token ASTRA_DB_API_ENDPOINT=your_astra_db_endpoint npx -y @datastax/astra-db-mcp
Note: ASTRA_DB_KEYSPACE is optional. If omitted, the default keyspace configured in the Astra DB library will be used.
Once added, your editor will be fully connected to your Astra DB database.
Available Tools
The server provides a comprehensive suite of tools spanning Collections, Vector Search, Tables, Keyspaces, and Administration:
📁 Collections & Documents
GetCollections: Get all collections in the active keyspaceGetCollectionInfo: Inspect collection options, vector settings, and default ID configurationCreateCollection: Create a collection with vector options, distance metrics (cosine,euclidean,dot_product), and auto-vectorize configurationsUpdateCollection: Update or rename a collectionDeleteCollection: Delete a collectionEstimateDocumentCount: Get an approximate count of documents in a collectionListRecords: List records with optional sorting, pagination (skip), and projectionGetRecord: Get a specific record by IDCreateRecord: Insert a single documentUpdateRecord: Update a recordDeleteRecord: Delete a record by IDFindRecord: Find records by exact field value matchFindWithFilter: Rich querying with MongoDB-style filter operators ($and,$or,$gt,$in,$exists, etc.)FindDistinctValues: Find distinct values for a specific field in a collectionBulkCreateRecords: Insert multiple documents in batchBulkUpdateRecords: Update multiple documents in batchBulkDeleteRecords: Delete multiple documents in batch
🧠 Vector Search & Reranking
FindWithVector: Dense vector similarity search with optional metadata filters, similarity scores, and projectionFindWithVectorize: Natural language search query using Astra DB Vectorize serverless embeddingsFindAndRerank: Hybrid search (lexical + dense vector / auto-vectorize) with server-side reranking scoresVectorSearch: Vector similarity search with minScore threshold and projectionHybridSearch: Combine dense vector similarity and text search with weighted scoring
📊 Tables (Astra DB Data API v2)
ListTables: List all structured tables in the keyspaceCreateTable: Create a typed table with column definitions and primary keysAlterTable: Add or drop columns (including vector columns)DropTable: Drop a tableQueryTable: Query table rows with filters, sorting, projection, and paginationInsertTableRow: Insert a single row or batch of rows into a tableUpdateTableRow: Update matching rows in a tableDeleteTableRow: Delete matching rows from a tableCreateTableIndex: Create a secondary index on a table columnCreateTableVectorIndex: Create a vector index on a table column with similarity metrics
🔑 Keyspaces & Administration
ListKeyspaces: List all keyspaces in the databaseCreateKeyspace: Create a new keyspace with optional automatic switchingDropKeyspace: Drop a keyspaceUseKeyspace: Switch the active working keyspace for subsequent operationsGetCurrentKeyspace: Inspect the active keyspace nameListEmbeddingProviders: Discover supported embedding models and providersListRerankingProviders: Discover supported reranking modelsGetDatabaseInfo: Retrieve environment metadata (ID, region, status, keyspaces)
🛠️ Utilities
OpenBrowser: Open a browser for authentication/setupHelpAddToClient: Assistance with MCP client installation
Changelog
All notable changes to this project will be documented in this file. The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
Running evals
The evals package loads an mcp client that then runs the index.ts file, so there is no need to rebuild between tests. You can load environment variables by prefixing the npx command. Full documentation can be found here.
OPENAI_API_KEY=your-key npx mcp-eval evals.ts tools.ts
