Typesense Vector Search MCP Server
Automate vector similarity searches via Typesense — index documents, manage collections, and execute semantic queries directly from your AI agent.
Vinkius AI Gateway suporta streamable HTTP e SSE.
Funciona com todos os agentes de IA que você já usa
…e qualquer cliente compatível com MCP
Typesense Vector Search MCP Server: veja o seu AI Agent em ação
Capacidades integradas (6)
create_collection
Provide the schema details as a JSON object. Creates a new search collection with a specific schema
delete_document
This action is irreversible. Permanently removes a document from a collection by its ID
get_collection_details
Retrieves schema and metadata for a specific collection
index_document
Provide the collection name and the document data as a JSON object. Adds or updates a document in a search collection
list_vector_collections
Lists all collections in the Typesense instance
search_vectors
Provide the collection name, a text query, and a vector_query string (e.g., "vec:(0.1, 0.2, ...)"). Performs a vector similarity search combined with optional text filtering
O que esse conector desbloqueia
Connect your Typesense Vector Search environment to any AI agent and take full autonomous control over vector collections, indexing processes, and semantic querying through daily conversation.
What you can do
- Vector Semantic Search — Issue combined text-filtering alongside vector similarity (
vec) queries natively through chat - Collection Provisioning — Instantly create new semantic schema datasets holding complex vector embedding structures organically
- Document Indexing — Let your AI insert or update JSON payloads into your database, bypassing manual code-level REST integrations
- Schema & Records Insights — Retrieve absolute schema geometries mapping collections to ensure developers map fields correctly
How it works
1. Subscribe to this connected MCP server
2. Provide your active Typesense Host URL alongside an Admin API Key
3. Start fetching vector similarities natively across Claude, Cursor, or your specific MCP workspace
No digging into CURL terminal payloads or writing Python scripts for basic document mutations. Your agent performs all indexation logic flawlessly.
Who is this for?
- AI Application Builders — prompt the agent to create semantic collections supporting
float[]logic seamlessly - Data Engineers — let the AI ingest missing RAG reference documents manually into a running collection
- Backend Devs — perform sanity checks and text-filtered semantic searches inspecting exact relevance scores
Perguntas frequentes
Dê aos seus agentes de IA o poder do Typesense Vector Search
Acesse o Typesense Vector Search e mais de 2.000 servidores MCP — prontos para seus agentes usarem, agora mesmo. Sem código cola. Sem integrações customizadas. Apenas plugue o Vinkius AI Gateway e deixe seus agentes trabalharem.
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