"Information on agent swarm architecture" matching MCP servers:

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

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.

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.

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.

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.

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.

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

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.

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.

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

An MCP server that provides data bridging from Spring Boot interfaces and a lightweight Python sandbox for script execution. It enables agents to fetch data as Markdown or Parquet files and perform automated data analysis within a controlled environment.

A metadata-guided, read-only SQL analysis MCP server for DataHub that helps agents perform safe analytical queries using DataHub schema, lineage, ownership, and tags, with a deterministic planner and strict SQL safety layer against local synthetic SQLite, guaranteeing zero write or mutation operations.

Enables querying cryptocurrency market data, refreshing data from CoinGecko, and performing market analysis through a FastMCP agent backed by a dlt pipeline and FastAPI.

Provides governed MCP tools for validating, explaining, and remediating clinical supply chain data quality across Bronze, Silver, and Gold layers on Azure Databricks, with data contracts and an evaluation harness.

Answers whether a route ran late and by how much, with drill-down into individual trip delays and an audit trail of data-quality exclusions and duplicate resolutions.