"Examples of DeepSeek-related applications or projects" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Ask your Odoo, PostgreSQL or MySQL data in plain words, from Claude, ChatGPT, Le Chat, VS Code or any MCP app. STYD runs read-only queries and answers with real numbers, the period and the definition it used. OAuth sign-in, sample data to try right away, and every answer names its workspace so data from different companies is never mixed.
Data Oil is a multi-model database built for object storage. It uses a log-structured storage engine, snapshot isolation with optimistic commit, and a change feed from the write-ahead log. Its SQL dialect supports joins, window functions, CTEs, set operations, graph traversal and pattern matching. It has its own HNSW vector index and BM25 full-text index, and a write is searchable by keyword and vector as soon as it commits. Access is over HTTP, the PostgreSQL wire protocol (extended protocol). We have a founder's program available for projects which may be of interest https://dataoil.tech/founders.html if your interested lets chat ;)
Turn Microsoft Fabric tables into an explainable graph and a GraphQL API. Understand how your Fabric tables fit together. See how your Fabric tables connect: the keys and relationships Krusgraph suggests, why, and what your data says, before a report or an app depends on them. A one-stop-shop for Data Engineering on Fabric
Single-digit millisecond search across vectors and text. At any scale, for fraction of the cost. https://warpsearch.io/
Every spreadsheet is a table: upload Excel, CSV, Parquet or JSON files and query them in SQL (Apache DataFusion), with joins across formats, schema and column statistics. Hosted tableski server; connect with your tableski.io access token. Open source: github.com/yarenty/tableski
Ask your AI assistant to sketch or change a Neo4j graph data model, then open it in toro4n.
ParseHub.dev is a hosted document-to-records service with a remote MCP server. Agents can upload a CSV, PDF, or Word file, summarize and analyze CSV data (filter, sort, group_by, and more), read text from PDF and Word files, extract attendees, agenda items, and action items from meeting notes, ask a question about an uploaded document, and store files as database records to list and read later. Each account sees only its own files and records. **Endpoint:** `https://parsehub.dev/mcp` (Streamable HTTP, stateless) **Auth:** API key in the `X-API-Key` header (keys start with `mcp_`), or `Authorization: Bearer <API key or JWT>`. Every request without credentials returns 401. **Plans:** Free (100 API requests/month, 1 document upload), or 5,000 requests/month on the $9/month or $42/year plan. Every MCP request counts toward the allowance. **Tools:** upload_csv, summarize_csv, analyze_csv, upload_document, read_document, extract_meeting_notes, ask_document, database_status, list_database_documents, get_database_document, store_document, extract_stored_meeting_notes, export_database (administrators only). Not affiliated with ParseHub (parsehub.com), the web-scraping tool. ParseHub.dev does not scrape websites. By Poietes LLC. Docs: https://parsehub.dev/guide#connect-via-mcp
It connects with Smart Data models database with more than 1000 open licensed data models and helps you to create applications and systems interoperable with existing standards or real applications
AMZScout Skill + MCP gives AI agents live access to real Amazon marketplace data across 14 Amazon marketplaces. Analyze any ASIN, validate product ideas, research niches, compare competitors, discover profitable keywords, and build data-driven PPC strategies using trusted Amazon insights instead of AI assumptions. Works with Claude, ChatGPT, Cursor, and any other MCP-compatible AI client. To connect, you'll need an AMZScout API plan and authorize your account. Get access and view pricing here: https://learn.amzscout.net/amazon-product-api-for-ai-agents
Backend for AI build SAAS applications - auth, dynamo db, functions, file storage, etc
Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.
Look up any Canadian drug product by brand name or DIN. Free drug_search tool.
Is a food, country or company in Japan MHLW imported food inspection orders? Rows as published.
Hosted backend for AI agents: create projects with persistent collections and keys, no signup.
Is this drug's shipment normal, limited or suspended in Japan (MHLW)? Hosted, history kept.
Push CSV, TSV, JSON, JSONL or Parquet from your agent and get a link a human can explore: filters, column charts, SQL, pinned findings and what changed since the last push. Viewing is free, no signup; anonymous datasets live 7 days. Tools: push, pin_finding, get_dataset, list_datasets, delete_dataset, get_limits. Docs: https://rows.page/docs/mcp
Sourced, dated records of family offices in Switzerland, Liechtenstein, Austria, Germany and Dubai.
Registry of companies selling AI agents identity, phone, email, addresses, money, legal, insurance
A unified biomedical graph database that integrates 50+ primary data sources — genes, proteins, compounds, diseases, pathways, and clinical data — into a single queryable graph with billions of cross-reference edges. Its native MCP server gives LLMs direct access to structured, authoritative biomedical data, complementing their reasoning with reliable identifiers and up-to-date database content.
The BigQuery remote MCP server is a fully managed service that uses the Model Context Protocol to connect AI applications and LLMs to BigQuery data sources. It provides secure, standardized tools for AI agents to list datasets and tables, retrieve schemas, generate and execute SQL queries through natural language, and analyze data—enabling direct access to enterprise analytics data without requiring manual SQL coding.
