SingleStore MCP. Run SQL, Search Vectors, and Audit Usage Directly.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
SingleStore MCP Server lets your AI client read and write directly to SingleStore. Execute raw SQL, run semantic vector searches against your data, list all workspaces, and audit billing metrics—all from one terminal connection.
What your AI agents can do
Execute sql
Runs a read-only SQL query against the SingleStore database.
Get billing usage
Retrieves current billing and usage metrics for auditing purposes.
List databases
Lists all databases contained within a specified workspace ID.
Your agent executes raw SELECT or modification statements directly against designated SingleStore databases.
The server runs a DOT_PRODUCT calculation to find data points semantically closest to a provided vector.
It retrieves and lists every SingleStore workspace associated with the account, providing necessary IDs for context.
The server pulls current operational costs and detailed usage figures from the platform's billing records.
It lists all databases contained within a specific, identified workspace.
Ask AI about this MCP
Supported MCP Clients
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SingleStore MCP Server: 6 Tools for Data & Admin Ops
Use these tools to allow your AI client to run complex database operations—from querying tables to managing server resources.
019d7608execute sql
Runs a read-only SQL query against the SingleStore database.
019d7608get billing usage
Retrieves current billing and usage metrics for auditing purposes.
019d7608list databases
Lists all databases contained within a specified workspace ID.
019d7608list organizations
Retrieves a list of organizations tied to the account structure.
019d7608list workspaces
Lists all existing SingleStore workspaces in the account.
019d7608vector search
Performs a semantic vector similarity search using dot product calculation.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with SingleStore, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
SingleStore MCP Server: Querying and Administering Databases
Listen, this server plugs your AI client straight into SingleStore. It makes your agent function like a full-time database admin, so you don't gotta jump around checking separate dashboards just to run queries or look at the schema details. You get direct access.
Data Querying and Semantic Search
Your agent uses execute_sql to fire off raw SELECT statements directly against your designated SingleStore databases, giving you read-only access to whatever data's sitting there. For searching beyond simple keywords, the tool runs a semantic vector similarity search, calculating the dot product to find data points that are semantically closest to any provided vector.
You can also use vector_search to perform these advanced lookups right within your workflow.
System Discovery and Context Management
You gotta know what you're dealing with before you write a query. The server first lets you check out all the containers using list_workspaces, which retrieves every SingleStore workspace associated with the account, giving you necessary IDs for context. Once you have that ID, list_databases shows you every database contained within that specific workspace.
To understand the full scope of your setup, list_organizations pulls a list of all organizations tied to the overall account structure.
Auditing and Administration
For keeping tabs on costs, get_billing_usage retrieves current billing metrics and detailed usage figures for auditing purposes. This lets you monitor operational costs straight from your agent connection.
How SingleStore MCP Works
- 1 You prompt your AI client to perform an action (e.g., 'Find the top 5 users who logged in last month').
- 2 The agent recognizes the intent and calls the
execute_sqltool, generating a specific SQL query tailored for SingleStore. - 3 The server executes the query against the database and returns structured results directly to your agent.
The bottom line is that you talk to your AI client in plain English, and it handles the complex API calls to get the data back.
Who Is SingleStore MCP For?
Database administrators, Data Engineers, and Analytics Developers. You're the person who spends half a day clicking through dashboards just to validate a single query or check if your team hit its usage limit. This server lets you run those checks programmatically via chat.
Uses execute_sql and vector_search to pull data for ETL jobs, validating schemas against the live environment without manual console logins.
Runs list_workspaces, list_organizations, and get_billing_usage to audit cluster health, check resource limits, or verify deployment scopes.
Uses the agent to combine metadata listing (list_databases) with raw SQL execution to build data validation scripts on demand.
What Changes When You Connect
- Automated Data Queries: Instead of writing a query in SSMS and running it manually, your agent executes
execute_sqldirectly. You get the results back into your chat window immediately. - Semantic Retrieval with
vector_search: Don't just search by keywords. Usevector_searchto find records whose meaning matches your input vector—it’s better than simple LIKE statements. - Centralized Infrastructure View: You can audit the entire environment using
list_workspaces, then drill down withlist_databases. It gives you a full map of where all your data lives. - Full Financial Visibility: The
get_billing_usagetool eliminates guesswork. You get precise usage metrics, allowing you to track costs without opening the billing console. - Reduced Context Switching: All necessary commands—from querying (
execute_sql) to listing metadata (list_organizations)—are available through one single connection point.
Real-World Use Cases
Validating Scope and Billing
An SRE needs to know if a new project was deployed in the correct cluster. Instead of checking the console, they prompt their agent: 'What workspaces do we have, and what is our current billing usage?' The agent runs list_workspaces then calls get_billing_usage, giving an immediate, comprehensive status report.
Deep Dive Data Validation
A developer needs to check the schema for a specific data set. They ask: 'List databases in workspace X.' The agent runs list_databases. Then they follow up with a targeted query, running execute_sql on the identified database to validate record counts.
Finding Related Knowledge
A researcher wants documents related to 'quantum computing ethics'. They don't know the right keywords. They input their vector embedding and the agent runs vector_search, returning semantically similar data records instantly, bypassing traditional keyword limitations.
Mapping Account Structure
A new team needs to understand all associated business units. They prompt: 'Show me all related accounts.' The agent executes list_organizations and then uses list_workspaces on the resulting list, mapping out the entire organizational structure in three steps.
The Tradeoffs
Assuming global visibility
Trying to run a query without knowing which workspace or database it belongs to, leading to vague errors like 'Resource not found.'
→
Always start by calling list_workspaces and then list_databases. This ensures your agent has the precise context required before attempting an execute_sql call.
Mixing up resource types
Attempting to use a search query when you should be listing metadata, or vice versa.
→
Use vector_search for similarity queries. If the goal is administration (like checking usage), run get_billing_usage. Keep the intent clear: Query vs. Audit vs. List.
Ignoring query constraints
Running complex, multi-stage logic in a single prompt that overwhelms the agent or hits permission limits.
→
Break tasks down. First, list the required workspaces using list_workspaces. Second, run the targeted data retrieval with execute_sql.
When It Fits, When It Doesn't
Use this MCP Server if your workflow requires an AI agent to perform both structured administration (listing resources, checking billing) AND live data manipulation (SQL queries, vector searches). It's essential when you can't afford context switching between a terminal, a dashboard, and a query builder.
Don't use it if:
1. You only need to read documentation—use the SingleStore console.
2. Your task is purely about writing boilerplate code or generating text outside of database interaction—your agent handles that fine without these tools.
3. You are using a different data source (e.g., Redis, S3)—you'll need a different MCP server for that.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by SingleStore. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 6 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Checking resource availability shouldn't require five clicks across three tabs.
Right now, checking if your team has permission to hit a specific data set requires navigating the main console, clicking 'Workspaces,' then searching for the cluster ID. Then you open the 'Billing' tab just to confirm resource limits—it’s a tedious copy-paste dance.
With this MCP server, you ask your agent: 'What are our available workspaces and current billing usage?' It runs `list_workspaces` and `get_billing_usage`, giving you an immediate, single block of text with all the IDs and metrics you need.
SingleStore MCP Server lets you get data—from simple tables to complex vectors.
Before this, if you needed a specific record, you ran `SELECT * FROM table LIMIT 10`. If you needed semantic context, you had to export the data and run it in an external vector client. It was disjointed.
Now, your agent handles both: it can query structured data using `execute_sql` or perform a meaning-based search with `vector_search`. You get two powerful functions consolidated into one chat interface.
Common Questions About SingleStore MCP
How do I list all the available SingleStore workspaces using the SingleStore MCP Server? +
Call the list_workspaces tool. This returns a comprehensive list of every workspace ID and name associated with your account, giving you the context needed for subsequent queries.
What is the difference between `execute_sql` and `vector_search` on the SingleStore MCP Server? +
execute_sql runs traditional SQL (e.g., 'select name from users'). vector_search takes a vector embedding and finds records whose meaning matches that vector using dot product.
Can I check my billing usage with the SingleStore MCP Server? +
Yes, you run the get_billing_usage tool. It pulls live metrics on your consumption and costs directly into the agent's output for immediate auditing.
Does the SingleStore MCP Server help me find databases in a workspace? +
You use the list_databases tool, providing it with a specific workspace ID. It returns all database names and IDs contained within that single scope.
When running complex queries with `execute_sql`, how does the SingleStore MCP Server handle potential database errors? +
The server reports specific error codes immediately. If your raw SQL query fails, the agent returns the exact database failure message and stack trace from SingleStore, letting you know precisely what needs fixing.
I need to see all my accounts; what does `list_organizations` provide about my overall SingleStore structure? +
It lists every organization associated with your account. This tool helps map out the boundaries of different client or departmental setups, ensuring you know which credentials govern which segment of your data.
For optimal results when using `vector_search`, what format should my input embeddings be in? +
The search expects a precise vector representation (typically an array of floats) that matches the dimensionality used to index your source data. Ensure the embedding model and the query inputs match dimensions for accurate DOT_PRODUCT calculations.
What limitations exist when I use `execute_sql` regarding read-only operations? +
While you have write capability, it's best practice to run read-only statements. The agent allows you to explicitly specify read-only queries to prevent accidental data modification and keeps your audit trail clean.
Can this execute a DROP TABLE query and delete my database? +
Yes! The execute_sql tool executes anything provided. Make sure to embed an API token that possesses read-only or strictly limited privileges to prevent accidental data destruction.
Are semantic vector searches natively supported? +
Absolutely. By utilizing the vector_search tool, your agent can issue DOT_PRODUCT evaluations seamlessly without needing external drivers.
Can I request my current billing and invoice costs? +
Yes. The get_billing_usage action explicitly pulls billing statements directly to the CLI interface for your specific cluster organization.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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