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The `hanzo` dispatcher hand-listed 10 services in SERVICE_TOOL_PATHS, so the other ~150 cloud products were unreachable until someone cut a Python release. Project the surface from cloud's /v1/openapi.json instead: cloud tags every operation with its product (the first path segment after /v1/), so that document already IS a service/action catalog. 166 services are now reachable, and a newly mounted app is callable the moment cloud serves it. Still exactly one MCP tool — agents degrade badly with hundreds — now shaped hanzo(service, action, params, method), with `services` listing the catalog and an empty action listing a service's actions. Delete the local Infinity vector store (3,546 lines). It shipped no embedder, so its only possible output was random vectors: it ranked "Bananas are yellow" above an auth document for the query "authentication oauth jwt". A previous fix put the mock behind HANZO_VECTOR_ALLOW_MOCK, but a fake that a flag can re-enable is still a fake, and a tool that lies to an agent is worse than a missing one. The package keeps only the cloud-backed VectorTool, and a test now fails if any module in it imports `random`. Make the legacy-tool gate honest: hide the per-service tools only once the unified tool genuinely imports. It does not import against released hanzo-tools (HanzoCloud is newer), and disabling them unconditionally would have left no cloud tools at all. - spec.py: catalog projection, cache keyed per spec source, stale cache beats failing a call. HANZO_OPENAPI_URL decouples catalog from target so a partial local host can be driven with the full registry. - HanzoCloud.call: one generic seam for the verbs the spec names (PUT/PATCH/ DELETE); auth also resolves the hanzo CLI's IAM session, memoized. - 40 new tests covering action naming, template binding, method inference, param split, and cache fallback. Co-authored-by: Hanzo Dev <[email protected]>
hanzo-tools-vector
Vector search and embedding tools for Hanzo AI MCP.
Tools
index- Project indexing for semantic searchvector_index- Create and manage vector embeddingsvector_search- Semantic search across indexed content
Installation
pip install hanzo-tools-vector
# With embedding models
pip install hanzo-tools-vector[full]
Features
- Semantic code search
- Document embedding and retrieval
- Project-aware indexing
- Multiple embedding model support
Usage
from hanzo_tools.vector import TOOLS, VECTOR_AVAILABLE, register_tools
if VECTOR_AVAILABLE:
register_tools(mcp_server, permission_manager)
Part of hanzo-tools
This package is part of the modular hanzo-tools ecosystem.