Oracle Vector DB MCP Server
Run vector similarity searches on Oracle 23ai — execute VECTOR_DISTANCE queries, inspect schemas, list vector indexes, and query tables from any AI agent.
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What is the Oracle Database MCP Server?
The Oracle Database MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Oracle Database via 7 tools. Run vector similarity searches on Oracle 23ai — execute VECTOR_DISTANCE queries, inspect schemas, list vector indexes, and query tables from any AI agent. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (7)
Tools for your AI Agents to operate Oracle Database
Ask your AI agent "Show me all tables in my schema that have VECTOR columns." and get the answer without opening a single dashboard. With 7 tools connected to real Oracle Database data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
Oracle Vector DB MCP Server capabilities
7 toolsDescribe table columns and explicit data types including VECTORs
WARNING: Output payload size is inherently limited, restrict rows fetched (FETCH FIRST 100 ROWS ONLY) to ensure stability. Execute arbitrary SQL query against the Oracle runtime via ORDS
Get exact Oracle DB Runtime version banner
List accessible tables in the current Oracle schema
List specialized AI Vector search indexes (HNSW, IVF) instantiated
Get table cardinality and optimizer statistics
1, -0.4, 0.5]` against a strict `VECTOR` column natively inside Oracle DB, sorting and fetching the nearest neighbors. Execute Vector similarity search via Oracle 23ai native VECTOR_DISTANCE
What the Oracle Vector DB MCP Server unlocks
Bring your Oracle Database 23ai vector capabilities directly into your AI agent workflow. Run VECTOR_DISTANCE similarity searches, inspect table schemas, execute SQL queries, and manage vector indexes — all through natural conversation.
What you can do
- Vector Similarity Search — Execute native Oracle 23ai VECTOR_DISTANCE queries with cosine or Euclidean metrics against any table with VECTOR columns
- Schema Inspection — List all tables in your schema and describe column types, spotting VECTOR-enabled columns for embedding storage
- SQL Execution — Run arbitrary SQL queries against Oracle via ORDS for ad-hoc analysis and data retrieval
- Vector Index Management — List all HNSW and IVF vector indexes instantiated across your tables
- Table Statistics — Get row counts and optimizer stats for capacity planning and query performance tuning
- Version Check — Verify your Oracle runtime version to confirm 23ai vector feature compatibility
How it works
1. Subscribe to this server
2. Enter your Oracle ORDS URL, Schema, Username, and Password
3. Start querying your vector store from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Enterprise data teams — run vector searches against production Oracle databases without context-switching to SQL Developer
- ML engineers — test embedding queries on Oracle 23ai's native vector engine during RAG pipeline development
- DBAs — inspect vector indexes, table stats, and schema configurations through conversation
Frequently asked questions about the Oracle Vector DB MCP Server
Does it work with Oracle Autonomous Database?
Yes. Oracle Autonomous Database on OCI has ORDS enabled by default. Use the ORDS URL from your ADB instance (e.g., https://xxxxx.adb.us-ashburn-1.oraclecloudapps.com/ords), your schema name (typically ADMIN), and the admin credentials. The VECTOR type is available on all 23ai-compatible instances.
Can I run arbitrary SQL — not just vector searches?
Yes. The execute_sql_query tool accepts any valid Oracle SQL statement and returns results through ORDS. Add FETCH FIRST N ROWS ONLY to keep payloads manageable. This makes the agent useful for relational queries too, not just vector operations.
Which distance metrics are available for vector search?
Oracle 23ai supports COSINE and EUCLIDEAN (L2) distance metrics natively via VECTOR_DISTANCE. Specify the metric when running a search — cosine is recommended for most text embedding use cases, while L2 works better for image or audio embeddings.
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Connect Oracle Vector DB with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
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Anthropic's agentic CLI for terminal-first development.
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Give your AI agents the power of Oracle Database MCP Server
Production-grade Oracle Vector DB MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.