Skip to main content
Glama
infino-ai

Infino MCP server

Official
by infino-ai

SQL over Infino

infino_sql

Run read-only SQL analytics with aggregates, joins, and filters, combining keyword, semantic, or hybrid search results in a single query.

Instructions

Use for structural or analytical questions — counts, GROUP BY, joins, aggregates, filtering by column value — returning result rows. The engine's search functions are callable as table-valued relations, so a single query can rank AND aggregate: bm25_search('table','text_col','terms', k) — also bm25_search_prefix / token_match / exact_match — need no embedding. vector_search('table','vec_col', {{q}}, k) and hybrid_search('table','text_col','terms','vec_col', {{q}}, k) need a query vector: put a {{name}} placeholder where the vector goes and pass embed:{"name":"query text"} — the server embeds the text and substitutes the vector in. Example: SELECT path, SUM(end_line - start_line + 1) AS lines FROM bm25_search('docs','body','error timeout', 300) GROUP BY path ORDER BY lines DESC. Read-only: a single SELECT / WITH statement; DDL/DML is rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
embedNoMap of placeholder name -> query text. Each text is embedded with the server's embedder and its vector is substituted for every {{name}} in the query — required to use vector_search / hybrid_search. E.g. {"q":"error timeout"} fills {{q}}.
queryYesA single read-only SELECT or WITH statement. May use search TVFs and {{name}} vector placeholders.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that the tool is read-only and that DDL/DML is rejected. It explains how search functions behave (table-valued relations, embedding requirement for vector/hybrid) and includes an example. This gives a clear picture of the tool's runtime behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is detailed but well-structured. It covers all necessary aspects without being redundant. While it is somewhat lengthy, the information is valuable and presented logically, with an example at the end.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (SQL with embedded search), the description is comprehensive. It explains the read-only nature, the syntax for search functions, the embedding workflow, and gives a concrete example. There is no output schema, but the description implies result rows, which is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaning to the query parameter by specifying it must be a SELECT or WITH statement, and to the embed parameter by explaining it maps placeholders to text that will be embedded and substituted. It also provides an example of the embed usage, enriching the schema information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool is for structural or analytical questions (counts, GROUP BY, joins, aggregates) and returns result rows. It distinguishes itself from the sibling search tools by framing it as a general SQL interface for queries that go beyond simple search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It says 'Use for structural or analytical questions' and explains the search functions are callable within SQL, implying when to use SQL versus the dedicated search tools. It also notes the read-only constraint, which is a usage guideline. However, it could be more explicit about when not to use SQL (e.g., for simple keyword retrieval, prefer the search tools).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/infino-ai/infino-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server