"Files" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
Unstructured document processing for LLM pipelines. Upload as PDF/DOCX/TXT any supported files, extract structured data (PII-redacted), build LLM-ready datasets, and search/export results — all via MCP tools (document.process, job.status, job.result, dataset.build, dataset.search, dataset.export).
Manage your Mistral platform — models, files, batch jobs, agents and RAG document libraries.
Generate 18 AI readiness files (llms.txt, ai.txt, RAG indexes, schema) for any website.
Rafter holds a team's durable knowledge — skills, agents and memory files, each versioned — and serves it to AI tools over MCP. Agents search across the team's artifacts before answering questions about how the team works or what was decided, fetch full artifact text along with its citation edges (cites, cited_by, links) to explore related material, and write new learnings back as memory. Also covers workspace, team and membership management.
MCP-native knowledge base for AI agents — vault-scoped docs, tables, and files, git-versioned, with hybrid search (BM25 + pgvector dense + reranker) and an event stream so external consolidators / gardeners stay decoupled.
The Needle MCP server enables semantic search on documents stored in files like PDFs, DOCX, and XLSX by connecting AI applications to external data sources. It provides capabilities to create and manage document collections, perform natural language searches on stored content, and retrieve relevant information without requiring exact keyword matches.
