Couchbase (Vector & NoSQL) MCP, Ready to Go
Use the Couchbase (Vector & NoSQL) MCP to let your AI agents run N1QL queries and KNN vector searches on your Couchbase cluster.
No credit card required. Experience the power of this integration risk-free.
Query NoSQL data and perform KNN vector searches on your Couchbase cluster.
Works with every AI agent you already use
…and any MCP-compatible client
How fast is the Couchbase (Vector & NoSQL) MCP Server?
Average time for the server to become ready for requests over the last 14 days, measured until the initialize / tools/list handshake completes. Metrics are updated daily between 00:00 and 04:00 UTC. Create a free account, use this MCP on Vinkius Cloud, and connect it to your AI agent in seconds.
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What AI agents can do with Couchbase (Vector & NoSQL) - 7 NoSQL & Vector Tools
Query NoSQL data, perform vector searches, and audit your Couchbase schema directly from your AI client.
List buckets
See all the routing spaces in your Couchbase DB. This helps you understand the high-level organization of your data.
List scopes
Find the limits and objects for your specific scopes and collections. It helps you see exactly what data is accessible.
List indexes
See all the active search indexes and rules attached to your data. This is vital for verifying your search configurations.
Execute n1ql query
Run N1QL queries to get specific JSON payloads from your buckets. It lets you perform complex data filtering using SQL-like logic.
Vector search
Map structural KNN vector similarities using your existing vector indexes. This is the core tool for similarity-based retrieval.
Get document
Pull internal properties for specific Couchbase KV documents using their keys. It gives you an exact look at a single record.
Fts search
Match query strings against your content trees using full-text search indexes. It handles structural text-based extraction.
One MCP enables access. Vinkius turns MCPs into production-ready infrastructure.
You're looking at one of 5,700+ managed MCPs. The real value isn't the catalog. It's the control plane that secures, governs, audits, and manages every interaction between your agents and the tools they use.
No Shadow AI
Every agent action is visible, approved, and auditable. Nothing runs outside your governance.
Absolute agent control
Fine-grained permissions for every agent, MCP, and tool. Instantly revoke access and audit every execution.
Cost control per token
Spend broken down to the token, tool, and agent. Budgets and hard limits. No surprise invoices.
Managed & monitored infra
We operate the runtime, authentication, scaling, retries, and monitoring. Your team manages AI, not infrastructure.
Data protection, DLP by design
Sensitive data is filtered before reaching the model. Access is governed so agents receive only the information they're allowed to use.
Token optimization, real savings
Lower AI costs by delivering the right context instead of unnecessary tools. Better accuracy, faster responses, and fewer wasted tokens.
Couchbase (Vector & NoSQL) for faster RAG development
This is for the engineers and architects who are tired of manual schema audits and the headache of debugging RAG pipelines. It's for people who need to move fast between data exploration and production deployment.
AI Engineer
Debugging vector similarity scores and refining RAG prompts by inspecting real-time data.
Data Architect
Auditing NoSQL structures and verifying collection organization across different environments.
Database Administrator
Monitoring search indexes and running N1QL queries to ensure data consistency.
Product Manager
Prototyping search features and checking JSON schemas without waiting on a dev ticket.
Frequently Asked Questions
Can I use the Couchbase (Vector & NoSQL) MCP to manage my RAG application? +
Yes. It allows your AI agent to perform KNN vector searches and N1QL queries, making it much easier to debug and refine how your AI retrieves information from your database.
Does the Couchbase (Vector & NoSQL) MCP work with my self-hosted cluster? +
It works with both Couchbase Capella and self-hosted clusters. You just need to provide your URL and credentials to give your agent access.
Can I use this to see my database structure? +
Absolutely. You can ask the agent to list your buckets, scopes, and collections to get a clear picture of how your data is organized without running manual commands.
Is the Couchbase (Vector & NoSQL) MCP good for auditing indexes? +
Yes, it's a great way to quickly enumerate all your search indexes and verify your vector definitions to ensure your search logic is set up correctly.
Can my AI agent actually run N1QL queries? +
Yes, the MCP allows your agent to execute N1QL queries and return the JSON results directly in your chat, saving you from writing and testing queries manually.
How do I connect my Couchbase data to my AI client using this? +
Once you subscribe on Vinkius, you just enter your database credentials. From there, your AI client can start querying your NoSQL and vector data immediately.
Can my agent perform K-Nearest Neighbor (KNN) vector searches in Couchbase? +
Yes. Provide the search index name, the vector embedding array, and the number of results (k). The agent uses Couchbase's native vector capabilities to locate the most semantically similar documents in your cluster.
How do I execute a N1QL query through the agent? +
Use the 'execute_n1ql_query' tool and provide your SQL-like statement. The agent will fetch the structural JSON blocks directly from Couchbase, allowing you to perform complex data retrieval using familiar SQL syntax.
Can I search documents using full-text query logic? +
Absolutely. The 'fts_search' tool leverages Couchbase's Full-Text Search (FTS) engine. Provide an index name and a boolean query string to perform structural text-based extraction across your document trees.
Your AI, connected to everything.
No credit card required · Free tier available
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