"Information about agents or agent-related topics" matching MCP servers:

Enables AI agents to inspect, query, test, and safely fix dbt projects and BigQuery warehouses under policy-enforced controls, with read-only direct queries and dbt-only allowlisted writes.

Enables ingestion of HL7 v2, ASTM, and JSON control results, Westgard multirule evaluation, automatic patient-result holds, explainable root-cause investigation, and supervisor-approved CAPA workflows for clinical laboratories. Agents can also establish targets, compute Levey-Jennings and sigma statistics, and verify corrective actions before a supervisor lifts a hold.

Enables AI agents to discover and query enterprise knowledge documents and business metrics through standardized MCP tools, supporting retrieval, structured sales/order analysis, anomaly scanning, and data lineage lookups.

Enables AI agents to search data sellers and datasets across categories, inspect sellers and data points, and request purchases, samples, or unlisted data without an API key.

Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.

Enables natural-language battery-cell requirements to be parsed and routed to simulation backends, returning design forms and performance metrics while supporting calibration, thermal-runaway, COMSOL, and UI draft workflows.

Enables AI agents to explore a synthetic product-event dataset and answer questions about signups, trends, funnels, and property breakdowns using a small set of composable, self-describing tools that return precomputed totals and actionable error hints.

MCP server for cleaning messy CSV data via a single clean_csv tool. Uses an agentic workflow with rule-based or LLM planners to transform data safely.

MCP server that enables one-click BIM audits by chaining IFC statistics, validation, and quantity takeoff workflows through natural language queries.

An autonomous MCP server that fetches datasets from IPFS/Filecoin, performs computation (anomaly detection, statistics, data quality scoring), and stores results via Multi-Chain Storage simulation.

A stdio MCP server exposing a validate_emails tool that lets agents screen email lists without sending mail or probing SMTP, checking syntax, DNS/MX records, disposable domains, role accounts, free providers, typo suggestions, and SPF/DMARC. Each address comes back with a valid/risky/invalid/unknown verdict plus machine-readable reason codes so agents can clean leads and signups before outreach or import.

Enables autonomous agents and scraping pipelines to deduplicate high-throughput event streams, repair and validate gigabyte-scale JSONL data, retry HTTP/S requests with exponential backoff and header rotation, mimic Chrome/Safari TLS fingerprints, and sync cross-domain cookie sessions. Tool invocations are metered through x402 USDC micropayments on Base L2, returning a payment challenge until a signed transaction unlocks execution.

An MCP server that exposes Estuary Flow pipeline operations as typed tools, enabling agents to inspect pipeline health, publish captures and materializations, edit/restart tasks, and read landed documents via tool calls.

Enables natural language interaction with JSON files, providing tools to load, query, aggregate, transform, and export data directly from AI editors.

Bring professional data to the AI you already use. QVeris connects AI assistants and workflows to services for company financials, social media, life sciences, research, patents, and e-commerce. Discover services, review scope and pricing, call them, and audit usage through one MCP connection. Requires a QVeris API key; charges depend on the selected service.

Enables agents to answer analytics questions with provable correctness by resolving metrics through the semantic layer, tracing lineage, traversing knowledge graphs, checking freshness, and searching glossary definitions, while enforcing access controls and logging every call.

Data observability for AI agents. Query alerts, monitor freshness, investigate schema drift, and trace lineage across your data warehouse via 53 MCP tools.

Transforms high-level business intents into structured Data Product Requirement Prompts through AI-powered conversational refinement. Guides users through clarifying questions to gather comprehensive requirements for automated Business Intelligence dashboard generation.

Enables analysis of raw SEO data by ingesting nested JSON datasets and converting them into clean, actionable metrics through the Model Context Protocol.

Enables querying financial balances, transactions, monthly breakdowns, anomalies, and cash forecasts for a vacation rental, plus creating validated manual entries with confirmation and audit logging.

A data governance agent that audits PostgreSQL databases through controlled MCP tools for schema inspection, null profiling, and anomaly detection.

Middleware that converts existing APIs/DBs into MCP tools with secure credential injection, data scoping, and immutable audit logs.

MCP server that parses legacy relational database schemas (Oracle, DB2, MySQL, MSSQL) and transpiles them to PostgreSQL with generated Prisma schema and TypeScript query helpers.

Enables verifiable business intelligence over federated data sources, supporting semantic queries, drill-down to source rows, and raw SQL with explicit verification status.

An MCP server that answers natural-language questions over CSV, Excel, and SQL data by providing deterministic tools for loading, profiling, querying, cleaning, statistical analysis, visualization, and reporting. It enables LLMs to plan and interpret while all computation is done exactly through MCP tools.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

An MCP server that enables LLMs to generate high-quality SVG charts using matplotlib, supporting various plot types like line, bar, and heatmaps. It provides flexible configuration for dimensions and axis scales, returning either raw SVG content or paths to saved image files.

Enables AI assistants and editors to profile, clean, and analyze messy CSV/Excel files directly through MCP tools such as profile_dataset, clean_dataset, and list_sheets.

Lets coding agents run governed SQL against a Databricks SQL warehouse and inspect Unity Catalog metadata over stdio or Streamable HTTP, with persistent operational logs stored in SQLite. Access is read-only by default and bounded by the configured identity's Unity Catalog permissions.

Turns natural language into data pipeline actions using six specialist agents that collaborate through MCP to build, validate, and monitor data infrastructure.