Weaviate MCP Server (Official)

Official Weaviate MCP server from Weaviate enabling AI agents to interact with Weaviate vector database — performing semantic search and hybrid queries, managing collections and objects, executing near-vector searches, and integrating Weaviate's AI-native vector database into agent-driven RAG, semantic search, and knowledge base workflows.

Evaluated Mar 06, 2026 (0d ago) vcurrent
Homepage ↗ Repo ↗ Developer Tools weaviate vector-database semantic-search mcp-server official rag embeddings
⚙ Agent Friendliness
78
/ 100
Can an agent use this?
🔒 Security
80
/ 100
Is it safe for agents?
⚡ Reliability
76
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
76
Documentation
82
Error Messages
75
Auth Simplicity
80
Rate Limits
78

🔒 Security

TLS Enforcement
90
Auth Strength
80
Scope Granularity
72
Dep. Hygiene
78
Secret Handling
78

TLS enforced for Weaviate Cloud. API key auth. SOC2, GDPR. Official Weaviate MCP. For self-hosted: configure TLS. Protect API key as secret.

⚡ Reliability

Uptime/SLA
80
Version Stability
75
Breaking Changes
75
Error Recovery
73
AF Security Reliability

Best When

An agent needs vector-based semantic search or RAG over a Weaviate collection — for knowledge base queries, similar document retrieval, or AI-native data access.

Avoid When

You need relational SQL queries, or you're using Pinecone/Qdrant/Chroma — those vector databases have their own MCPs with better coverage.

Use Cases

  • Performing semantic search over vector-embedded content from RAG agents
  • Running hybrid (vector + keyword) searches from search agents
  • Managing vector collections and ingesting documents from data pipeline agents
  • Building knowledge bases for agent memory from AI application agents
  • Querying similar items by vector proximity from recommendation agents
  • Exploring collection schema and vector space from data discovery agents

Not For

  • Teams using Pinecone, Qdrant, or Chroma for vector storage (use those MCPs)
  • Relational data queries (Weaviate is vector-first, not relational)
  • Teams not using embedding-based similarity search

Interface

REST API
Yes
GraphQL
Yes
gRPC
Yes
MCP Server
Yes
SDK
Yes
Webhooks
No

Authentication

Methods: api_key oauth2
OAuth: Yes Scopes: No

Weaviate Cloud uses API key authentication. Self-hosted supports no-auth (dev) or API key. OpenID Connect (OIDC) for enterprise. Weaviate Cloud connection URL + API key is standard configuration.

Pricing

Model: freemium
Free tier: Yes
Requires CC: No

Weaviate Embedded (local) is free. Weaviate Cloud offers sandbox for development. Production clusters require paid plan. Self-hosted Weaviate is open source and free.

Agent Metadata

Pagination
cursor
Idempotent
Partial
Retry Guidance
Not documented

Known Gotchas

  • Vectors must be pre-generated or use Weaviate vectorizer modules — not automatic
  • Weaviate GraphQL query syntax is specific — not standard GraphQL; agents need Weaviate-specific patterns
  • Collection schema must define vectorizer and properties before ingesting data
  • Near-vector vs near-text searches have different behaviors depending on configured modules
  • Weaviate v3 (Python client) vs v2 have different API patterns
  • Official Weaviate MCP is newer — verify feature coverage for your use case

Alternatives

Full Evaluation Report

Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for Weaviate MCP Server (Official).

$99

Scores are editorial opinions as of 2026-03-06.

5220
Packages Evaluated
26151
Need Evaluation
173
Need Re-evaluation
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