Provision a managed database or storage addon (Postgres, Redis, S3) in a Lizard project. Each call creates a new addon, never updates an existing one.
MIT
569,792 tools. Updated 2026-09-15 02:36
"An MCP server for indexing S3 content into a RAG vector database" matching MCP tools:
- Index a dataset so text chunks become searchable. Splits content into RAG-ready chunks and generates embeddings for semantic retrieval.MIT
- Get a high-level summary of MCPg's capabilities, organized into buckets like schema introspection and query execution. Returns version and tool recommendations. Read-only; no database access.MIT
- Scrape a public URL to create a searchable knowledge base. Extracts content from web pages (including JavaScript-rendered), chunks it, and indexes for RAG.MIT
- Convert a website or up to 1000 URLs into RAG-ready chunked JSONL for vector database import.MIT
- Upload files to a durable knowledge store for indexing, so they become searchable across RAG queries. Provide a bucket destination and file content either by local path or base64.MIT
Matching MCP Servers
- -licenseNot gradedqualityCmaintenanceTurn SEC EDGAR filings into a searchable vector database, enabling natural language queries over company filings through Claude Desktop.-
- AlicenseAqualityDmaintenanceA Model Context Protocol (MCP) server for AWS S3 integration using FastMCP and boto3. This server provides access to S3 functionality through MCP-compatible tools.101MIT
Matching MCP Connectors
MCP server for social media and content data including social profiles, engagement metrics, content trends, and influencer analytics for AI agents.
Apple Developer Documentation with Semantic Search, RAG, and AI reranking for MCP clients
- Keep RAG search current by re-indexing catalog schema after changes. Uses schema hashing to skip unchanged schemas.Apache 2.0
- Add an evidence bundle to a collection for semantic search and Q&A. Triggers async vector indexing; poll job status until complete.MIT
- Bulk-load vectors from a CSV/delimited file into a vertex type's vector attribute by creating, running, and dropping a GSQL loading job.Apache 2.0
- Create an empty RawTree table in a database, optionally using a customer-owned S3 bucket for data and backups. Returns the resolved storage destination.MIT
- Bulk-load vector embeddings from a JSON Lines file into a TigerGraph vertex attribute by creating and running a GSQL loading job.Apache 2.0
- Ingest a PDF, DOCX, TXT, or MD file into a local vector database for semantic search. Re-ingesting the same absolute path replaces existing data.MIT
- Generate vector embeddings from text for semantic search, RAG, clustering, or similarity tasks. Choose between query or document input type and adjust model quality and dimensionality.MIT
- Convert text into a numeric vector for semantic search, RAG, and similarity. Supports multiple languages.MIT
- Upload 1–100 knowledge files in one request to the Calypso RAG knowledge store for bulk indexing, with batch status polling until ready.MIT
- Add a bucket-scoped S3 connection to an endpoint, providing client, data, web, and public S3 contexts for file operations.Apache 2.0
- Trigger a metadata scan on an S3 bucket to index its objects into ObjectLens, enabling search and preview.Apache 2.0
- Retrieve current connection status, latency, and version details for Memory Server, RAG Server, and Google services to verify service availability.MIT
- Extract clean content from a public URL, returning Markdown, text, metadata, links, JSON-LD schema, and sections for scraping, RAG ingestion, or content analysis.MIT
- Create a vector index on a vector field in Baidu Vector Database to enable efficient similarity searches for AI applications.Apache 2.0
- Integrate a Milvus vector database into an endpoint's context, enabling vector search operations through ctx.MILVUS.Apache 2.0