SEAM: local-first memory runtime for AI agents, with retrieval and glassbox provenance over MCP.
Embeddings and similarity search.
SEAM: local-first memory runtime for AI agents, with retrieval and glassbox provenance over MCP.
Your agent seeks what search can't find. A self-hosted perception MCP server.
Universal web content extraction — any URL to LLM-ready markdown. HTML, YouTube, PDF, DOCX.
Local semantic search — embedding-powered grep for files, zero external services.
Local-first RAG engine with MCP server for AI agent integration.
AST-based semantic code search; results ship with their call graph (calls + callers).
Execute KQL in AI prompts via NL2KQL with schema discovery and Azure Data Explorer integration
Governed support MCP: answers only KB-grounded questions with citations, escalates the rest.
No-code platform for building 24/7 AI voice agents. Configure an agent in plain text, attach a phone number in 70+ countries, deploy to phone, web widget, or WhatsApp. 1000+ voices across 90+ languages with sub-200ms latency.
Unified AI model gateway. One OpenAI-compatible endpoint for every major model (OpenAI, Anthropic, Google, DeepSeek, and more) with automatic failover and intelligent routing.
A private, end-to-end-encrypted notebook that acts as secure long-term memory for AI agents. Create, search, and organise notes on a user's behalf.
Agent-controllable markdown workspace. Folders hold .md documents an AI agent can read, create, update, organize, and share. Control it via the MCP server (preferred) at https://mdflow.cz/api/mcp or the REST API at https://mdflow.cz/api/v1, authenticating with a Personal Access Token (requires MDfl…
Local-only MCP server for source-attributed Markdown memory and documentation retrieval.
Semantic code search built for AI agents. Hybrid, AST-aware, context for 166 languages.
Semantic search for Historical Soundscapes. Search eventos, entities, filters. Cross-lingual ES/EN.
Apple Developer Documentation with Semantic Search, RAG, and AI reranking for MCP clients
Recognition-first cross-agent memory federation. One shared memory across all your agents.
Project memory, semantic code search, and grounded agent context.
Graph-vector memory for AI assistants using FalkorDB and Qdrant
Fleet discovery for the cyanheads MCP ecosystem — semantic search + install snippets.