Enables structured document understanding of local PDFs via a dual-extract MCP server, combining MinerU text/layout and Qwen3-VL vision with fusion adjudication for field extraction, tables, formulas, and validation. Fully local and offline.
Enables read-only collection and comparison of Google Search Console and Bing Webmaster data, conservative URL protection, content auditing, reviewed-build verification, and private report generation through ten typed tools over stdio.
Connects MCP clients to databases like Snowflake, BigQuery, and Databricks through Alkemi's data platform, enabling natural language database queries with proper schema understanding and metadata management for consistent team-wide access.
Enables MCP clients to connect document sources, prepare searchable documents, and run RAG-ready lexical, vector, or hybrid search with account-scoped document access.
Enables agents to synchronize, merge, and reconcile distributed state across nodes using conflict-free last-write-wins element sets with Lamport/vector-clock causality, token-bucket gossip dissemination, and quorum-based commit coordination. It runs entirely on the Python standard library and exposes these primitives to Claude Desktop, Cursor, and Windsurf over the MCP JSON-RPC stdio protocol.
MCP server with 32 tools for ETL ingestion, AI-generated data quality rules, AI
transformations, vector search, and natural-language SQL. Works across Postgres,
MongoDB, Kafka, S3/MinIO, HashiCorp Vault, and five vector stores
(Qdrant, Weaviate, Milvus, Chroma, pgvector).
Unifies Google Search Console, Bing Webmaster Tools, GA4, and PageSpeed APIs behind one MCP server, letting an agent join search, indexing, and analytics data across providers while staying read-only and boundary-limited by default.
Syncs Google Search Console performance data into a local ClickHouse database and exposes prepared SEO analysis tools to AI agents. Enables diagnosing traffic drops, finding striking-distance keywords, detecting cannibalization, auditing indexing, and generating weekly SEO reports through natural language.
Provides deterministic tools for understanding, transforming, and verifying structured data via MCP, enabling rule inference from examples and verification of transformed records.
Enables AI clients to read and describe ArcGIS geodatabase, shapefile, and raster data, run vector geoprocessing, editing, statistics, cartography, and format-conversion tools through a local ArcPy worker, and trace the lineage of derived datasets and background jobs. It supports both Streamable HTTP and stdio transports, with copy-before-edit, staged publishing, and workspace locking for data protection on a trusted local machine.
Transforms CSV and Excel data into Markdown-formatted vector embeddings stored in a local ChromaDB instance for semantic search. It enables MCP clients to retrieve relevant tabular data through single-row, batch, or free-text queries.
Exposes an agentic AutoML pipeline as a callable tool so any MCP client can upload a CSV and natural language goal and receive a full ML analysis report with SHAP visualizations. Enables autonomous problem understanding, data cleaning, feature engineering, model training, and explainability through a single remote tool call.
Deterministic encode, decode, hash and convert for agents, on the same pipeline engine as the String Utility Belt web app, CLI and editor extensions: a pipeline built and checked in the browser runs unchanged from its share link. Base64/hex/URL, JWT, hashes, JSON/YAML/CSV/XML, dates and regex; tools to search, describe and run utilities or whole pipelines, and to detect input formats. Runs locally
Enables clients to interact with PipesHub data and functionality through MCP, including chat, search, record retrieval, directory browsing, sources, and agents.
Enables environmental scientists to tidy PFAS lab files, screen results against two drinking-water guideline sets side by side, search public guidance with page-level citations, and check report text so every number traces back to its lab row or guideline page.
An MCP server that converts Apache Airflow DAGs into Prefect flows. It provides tools to read DAGs, lookup translation knowledge, validate code, search Prefect docs, scaffold projects, deploy, and generate migration reports.
Enables AI agents to discover and access 800TB+ of public geospatial data from Source Cooperative, with tools for listing organizations, products, files, and fuzzy search.
Enables MCP clients to search and inspect a catalog of 125 commerce, inventory, and data skills, invoke them with explicit spending limits, and check wallet balances and receipts.
An MCP server for college placement cells to analyze student profiles from bulk Excel data, search students, and access evidence-backed skill intelligence from resumes, GitHub, LeetCode, and portfolios. It provides tools for skill gap analysis and profile completeness evaluation.
Enables AI assistants to search multiple tech job boards at once, summarize what the market is asking for, and rank postings by how well they match a user's own skills.
Self-hosted financial data terminal for AI agents. Scrapes and serves SEC filings (full-text search), 13F institutional holdings, insider and congressional trades, FINRA short data, FRED economic indicators, CFTC futures positioning, VIX/put-call ratios, and daily stock prices over MCP.
Search Redfin for-sale, for-rent, and sold listings with Redfin's full visitor filter set, and retrieve complete property pages as structured JSON, through any MCP client and without an MLS license.
Enables AI agents to search, correlate, and monitor real-time vulnerability intelligence from NVD, CISA KEV, EPSS, and MITRE ATT&CK, including CVE details, critical CVE tracking, known exploited vulnerabilities, and exploitation probability scores.
Enables AI agents and assistants to work with a Databricks workspace — SQL, clusters and warehouses, notebooks, Jobs, Lakeflow pipelines, Unity Catalog, Volumes, dashboards, Genie, model serving, Vector Search, Lakebase and Apps — under a safety-first model with read/write/destructive/security classification, confirmation steps for dangerous changes, production resource protection, and a fully read-only mode. Every call is checked against the official Databricks SDK, returns typed schemas and redacted secrets, and unsupported features report an explicit error rather than faking results.
Turns messy real estate data into clean, scored, AI-ready property intelligence for Columbus, OH metro, with pay-per-query via x402 micropayments. Enables natural-language search, investment scoring, and enrichment tools for MCP clients.
Imports CSV or Excel files into Dynamics 365 Finance & Operations data projects through the Data Management Framework, generating manifests, resolving entity targets and dependency order, and waiting for execution results. Also exports data projects and exposes tools to search the entity catalogue, inspect entity fields, and check execution status.
