"Current oil price lookup" matching MCP servers:

Enables MCP clients to ingest invoice PDFs into a hybrid-chunked FAISS index, semantically search them, and extract typed invoice data with deterministic arithmetic validation. It also provides listed-company financials and current web search results so agents can research vendors.

Enables AI clients like Claude Desktop and Cursor to persist project knowledge across sessions and tools by extracting durable facts from conversations, deduplicating them, resolving contradictions, and retrieving only the most relevant, token-budgeted facts for the current task. Adds PII redaction, project scoping, TTL-based staleness handling, and an append-only audit log so shared context stays current and safe.

Enables an LLM to maintain and query durable layered context across sessions, retrieving standing rules, current state, open loops, compiled pages, historical facts, and hard records with explicit conflict handling and abstention when nothing matches.

Enables AI assistants to retain atomic facts, decisions, and episodic lessons in a persistent shared SQLite graph memory, then recall them through hybrid BM25 plus dense-vector search with spreading activation and progressively packed context. Also supports reflection-based belief revision so stale or contradictory memories are superseded rather than returned alongside current ones.

Enables AI coding assistants to automatically scan, store, and query API endpoints from codebases, providing instant lookup and semantic search to reduce context switching and token consumption.

Enables coding agents to persistently store memories, artifacts, and context discarded by compaction into a searchable store, then automatically recall and inject the items relevant to the current task. It fuses BM25 keyword search with embedding-vector retrieval so differently-phrased memories still match, running as a fail-open sidecar that never blocks the agent session.

Enables semantic search and exact retrieval of banking document evidence from Supabase pgvector, with tools for BRD/RCA document filtering and previous RCA lookup.

Enables LLM-based agents and MCP-compatible clients to perform full CRUD operations on FHIR resources, plus AI-powered document ingestion, semantic search, and LOINC terminology lookup. Users can query and manipulate clinical data using natural-language prompts.

Enables LLM-based agents and MCP-compatible clients to interact with FHIR-compliant backends through full CRUD operations, document ingestion, semantic search, and LOINC terminology lookup. It supports natural-language querying and manipulation of clinical data.

Enables LLM-based agents and MCP-compatible clients to interact with FHIR-compliant backends through natural-language prompts, supporting CRUD operations, clinical data queries, document ingestion, semantic search, and LOINC terminology lookup. It also provides secure authentication and RAG-ready document retrieval.

Enables LLM-based agents and MCP-compatible clients to query and manipulate clinical data through natural-language prompts by providing full CRUD operations on FHIR resources, document ingestion, semantic search, and LOINC terminology lookup.

An institutional-grade algorithmic trading platform that bridges MetaTrader 5 with an autonomous AI cortex for high-frequency data extraction, ML-driven analysis, and autonomous decision-making using the FEAT methodology.

Enables semantic search across documents and code repositories using RAG (Retrieval-Augmented Generation) with vector embeddings. Automatically indexes PDF documents and performs relevance-scored lookups through ChromaDB and sentence transformers.

Enables LLM-based agents and MCP-compatible clients to query and manipulate FHIR clinical data through natural-language prompts, with full CRUD operations, document ingestion, semantic search, and LOINC terminology lookup.

Enables LLM-based agents and MCP-compatible clients to interact with FHIR-compliant backends, performing full CRUD operations on clinical resources through natural-language prompts, with document ingestion, semantic search, and LOINC terminology lookup.

Enables semantic search and natural language product recommendations using ChromaDB vector store and Azure OpenAI embeddings. Supports multi-filter search by category, brand, and price with 8 specialized MCP methods for intelligent product discovery.

Enables LLM-based agents and MCP-compatible clients such as Claude Desktop to query and manipulate clinical data through natural-language prompts, supporting full CRUD operations on FHIR resources, OAuth2-secured FHIR API access, AI-powered document ingestion, and semantic search over embedded documents via Pinecone. It also provides LOINC terminology lookup and validation, plus RAG-ready context retrieval for clinical data workflows.

Tracks learning progress and generates personalized daily learning insights using RAG to fetch relevant content from blogs, RSS feeds, and Reddit based on your current topics and learning goals.