"postgres-mcp-pro" matching MCP servers:

A read-only MCP server that exposes dbt project artifacts and data quality result tables (BigQuery/Postgres) to LLM clients, enabling deep introspection, run-history analysis, source freshness, test coverage, and lineage walks.

Enables AI agents to create, manage, and monitor two-way data syncs between platforms like Airtable, Webflow, HubSpot, Salesforce, Notion, and Postgres, including mapping fields, running syncs, and troubleshooting record-level issues.

Enables DeepSeek Harness models to directly call local ArcGIS Pro via MCP tools for reading projects, layers, GDB structures, and executing Buffer/Clip/custom ArcPy operations locally.

Enables Claude to query a Postgres analytics schema via a read-only MCP server, with tools auto-generated from live database introspection and configurable SQL queries defined in YAML.

A PostgreSQL MCP server for AI agents that streams large result sets to CSV, enforces per-query timeouts, auto-reconnects with backoff, and supports long-running tunnel scripts with credential rotation.

Bridges JLCPCB/Lichuang EDA Pro with MCP clients to export and analyze schematic/PCB DRC, netlists, and BOMs, enabling automated diagnostics and data queries.

Provides MCP tools for scanning, redacting, and packaging dataset/model directories for public release, leveraging Presidio for PII detection and generating Hugging Face cards and EU AI Act training-data summaries.

Tracks buying and momentum signals for companies, such as funding rounds, senior hires, office openings, customer wins, and partnerships, with each event carrying its date.

Classifies job titles into department and seniority using deterministic rules, and optionally verifies if a person is listed on their employer's website via the Mamba Labs Contact Classifier Apify actor.

Enables agents to reconcile piping material take-offs against Plant 3D SCSA exports by previewing diffs and applying quantity corrections, insertions, and gated removals with dry-run and explicit confirmation flags.

Bridges Microsoft Clarity's analytics API with Claude, enabling custom date ranges and page-level filtering on top of Clarity's native limitations.

Enables clients to interact with PipesHub data and functionality through MCP, including chat, search, record retrieval, directory browsing, sources, and agents.

Connects your BitScale workspace to Claude, allowing you to manage grids, fetch row data, and trigger enrichment runs via natural language. It provides tools for listing grids, checking run status, and retrieving workspace details.

A read-only MCP server for querying SQL Server Analysis Services (multidimensional cubes via MDX and tabular models via DAX) using Windows Integrated Security.

Web extraction MCP server for AI agents. Extract structured data from any URL with built-in Cloudflare bypass, JavaScript rendering, and intelligent parsing. Returns clean markdown or JSON.

Provides tools for managing qualitative research knowledge graphs, enabling structured representation of research projects, participants, interviews, observations, codes, themes, and findings.

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

AgentShare delivers structured product search and pricing signals for AI agents over REST and MCP (Streamable HTTP). Responses include freshness & coverage metadata so agents can reason about data recency. API keys secure billed endpoints; public discovery at /agent.json and /mcp.json. Currently integrates connected marketplaces and affiliate feeds – roadmap expands to global e-commerce (AliExpre

Enables users to perform deterministic time series forecasting through Claude by running reproducible Python statistical and foundation models, providing tools for loading data, cross-validation, forecasting, anomaly detection, and exporting re-runnable manifests without any LLM involvement.

An MCP server that enables AI coding assistants to interact with a local Airflow cluster via its REST API for triggering DAG runs, monitoring status, reading logs, and diagnosing errors.