"An explanation or resources about vectors (mathematics, physics, programming, or graphics)" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Query your Postgres from ChatGPT or Claude without exposing the database or handing over credentials. Run npx boltschema connect next to your database and it dials out over HTTPS — no inbound firewall rule, no open port, works with localhost and VPC-private databases. Read-only is enforced by a SQL guard, a Postgres READ ONLY transaction, and a scoped role generated for you.
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
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
Interact with your Google Bigtable resources using natural language commands.
Create, manage, and query your Google Cloud SQL resources.
Interact with your Google Cloud Datastream resources using natural language commands.
Interact with your Google Cloud Firestore resources using natural language commands.
Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.
Connect Karma.Domains to ChatGPT, Claude, Cursor, VS Code, or another MCP client — and find a domain in plain language. The same auctions, expired, backorder, and buy-now data you use in the app, plus saved filters, notes and tags, guest share links, and SEO enrich — all from chat.
- ChrysaiOAuthcom.chrysai
Chrysai provides a hosted MCP server for AI-driven data operations. After connecting an MCP client to the endpoint, you can use MCP tools such as create_app, list_apps, read_data, write_data, update_data, delete_data, and update_app, plus schema resources, to manage persistent structured data through natural language.
Access comprehensive company data including financial records, ownership structures, and contact information. Search for businesses using domains, registration numbers, or LinkedIn profiles to streamline due diligence and lead generation. Retrieve historical financial performance and complex corporate group structures to support informed business analysis.
An MCP server for converting data between 16 formats including JSON, YAML, TOML, CSV, XML, Markdown, HTML, Excel, PDF, and more. Supports single transforms, batch fan-out to multiple targets in one call, and JSON reshaping with dot-notation path mapping. 240 conversion pairs, zero config.
Shared memory for AI agents, as a graph in your own Postgres. Writes never call an LLM.
Governed access to production AI-agent traces in an existing ClickHouse store.
Push rows from a dataset, file or Google Sheet into a Postgres, Supabase, Neon or MySQL table.
Add fast, typo-tolerant search to your site or app, and run the Typesense clusters behind it.
- SIGNLDOAuthai.signld.app
Gives an agent read-only access to a SIGNLD workspace: list data connections and table schemas, run read-only SQL over the data, and read the knowledge graph, entities, metrics, and topics. It can also create and update knowledge graph elements and topics, build charts from query results, and save standalone HTML dashboards.
The Instant MCP server is a wrapper around the Instant Platform SDK that enables creating, managing, and updating InstantDB applications directly within an editor. It provides tools for fetching rules files for LLMs, retrieving and pushing app schemas, managing permission rules, and executing database queries. Key capabilities include schema management (get-schema, push-schema), permission management (get-perms, push-perms), query execution, and listing recent query history.
Read and edit DB Planner database schemas, diagrams and board layouts as an AI agent.
Put an AI-written project online: a site on a subdomain with a Postgres database of its own.
