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"Information about SQL (Structured Query Language)" matching MCP tools:

  • Run a read-only SQL query against an app's Postgres database and return up to 200 result rows. SELECT only — writes and DDL (INSERT/UPDATE/DELETE/ALTER/DROP/…) are rejected server-side; use vibekit_chat or vibekit_submit_task to have the agent make data or schema changes. Call vibekit_db_schema first to learn the tables. SQL string, max 5000 chars.
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  • Translate a plain-language question into a candidate SQL query using pattern-matching against the live schema (no AI model — simple questions only: counts, averages, filtered selects on a named table). Returns the SQL without executing it, with a confidence score; low confidence means the table was guessed. Review the statement and tables_used, then run it with scalix_db_query. For complex questions, read scalix_db_schema and write the SQL directly.
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  • Execute a structured query against connected data sources. Convert the user's question to a structured intent and call this tool — do NOT try to write SQL or parse column names yourself. The engine resolves column meaning from mathematical relationships and statistical structure only. It works on any dataset without configuration. The governed filter shape is a record-predicate contract over normalized rows, not a SQL predicate language, so it also applies to Redis and other non-SQL sources. Structural roles (use in metric.role): - derived_measure: the main financial/operational aggregate (revenue, spend, value) - base_measure: counts, quantities, discrete amounts - unit_measure: per-unit prices, rates - ratio: percentages, margins, fill rates (0-1 range) - metric: let the engine pick the best numeric column If clarification_required is true, or if confidence < 0.85, check the candidates list and ask the user to clarify. Never fabricate column names or SQL.
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  • Search for SecDim Play secure coding labs (hands-on, scored challenges). This tool searches across SecDim Play's hands-on secure coding labs based on the search query. The backend API handles parsing of vulnerability names, CWE IDs, and OWASP IDs. Language can be specified using the format "lang:javascript". Args: query: Search query that may include: - Vulnerability names (e.g., "XSS", "SQL injection") - CWE IDs (e.g., "79") - OWASP IDs (e.g., "A03:2021") Examples: - "XSS lang:javascript" - searches for XSS labs in JavaScript - "SQL injection lang:Python" - searches for SQL injection labs in Python - "79" - searches for labs related to CWE-79 Returns: Dictionary with search results containing: - results: List of matching SecDim Play labs with id, title, snippet, and metadata
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  • Execute a constrained read-only SQL rowset query over authorized datasets. Use this only for wide reports that do not fit the governed exact-query surface. SQL must be a single SELECT/WITH statement over the provided dataset aliases.
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  • Enrich a B2B company profile with structured firmographic, technographic, intent, and contact data. This tool should be called when an AI agent needs to gather detailed information about a company before crafting a personalized outreach, generating a lead score, or making a sales recommendation.
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Matching MCP Servers

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    An MCP server providing SQLite database access for AI agents, enabling SQL execution, schema inspection, CRUD operations, and data export.
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    MIT

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  • Architecture-grounded query for AI agents. Governance constraints, system dependencies, evidence.

  • A fully autonomous, Agent-to-Agent (A2A) patent data marketplace powered by the Model Context Protocol (MCP) and A2A standards. This server provides highly structured, AI-optimized JSON patent datasets curated for autonomous R&D agents, LLMs, and Quants. Currently exclusively hosting AI-ready patents from IPC/CPC Sections G (Physics & Computing) and H (Electricity).

  • Run a custom JQL (JavaScript Query Language) script for arbitrary analysis. Power-user escape hatch. Script must define main(). Query API: POST /jql. (Upstream maintenance mode; 2-min timeout, 5GB/query limit.)
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  • Get the machine-readable Algenta public contract. Use this when an agent needs the canonical discovery, summary, query, batch, SQL report, governed filter rules, CLI, or MCP entrypoints before planning tool use.
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  • Run an arbitrary HogQL (SQL) query against PostHog data. Use for custom analysis not covered by other tools. Only works if PostHog is connected.
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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Query the construction project database using natural language (Text-to-SQL). Converts natural language into SQL to retrieve captures, annotations, progress metrics, schedules, and other project records. Pass the user's question as-is without modification. For trade visibility, use `analyze-progress-and-forecasts` instead. **WORKFLOW:** - **Default**: call this tool with only `query`. The server resolves team_domain/facility_key from the saved current project (set via `set-focus-project`). Do NOT call `list-my-projects` again just to obtain these values. - Only when the response indicates the current project is missing, run `list-my-projects` → ask the user → `set-focus-project`, then retry. - Pass explicit team_domain/facility_key **only** when the user clearly wants to query a different project than the saved one. **Available tables:** - progresses: SI progress metrics (level, category, phase, workarea, cost, dates) - captures: Camera captures metadata (level, camera_model, capture_state, user_email) - records: Capture events with timestamps (captured_at, state, id) - photo_notes: Photonotes (description, state, user_email, created_at) - voice_notes: Voicenotes (level, description, state, user_email, created_at) - facilities: Site info (name, address, size, location, bim_count, created_at) - users: User profiles (name, email) - workareas: Spatial zones (level, name, user_name) Args: query: Natural language question (pass as-is, no SQL syntax) team_domain: Omit by default. Pass only to override the current project. facility_key: Omit by default. Pass only to override the current project. user_intent: REQUIRED. Pass the user's original question or request verbatim. Used for analytics only, does not affect results. Returns: List of TextContent with query results and metadata
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