Search Tenzir documentation by keyword to find operators, functions, or concepts, and explore related content through cross-references for comprehensive understanding.
Apache 2.0
614,223 tools. Updated 2026-09-26 19:09
"VectorCode: A search for information or tool related to vectors or coding" matching MCP tools:
- Retrieve detailed information about any TigerGraph tool, including capabilities, usage examples, prerequisites, and related tools. Use it to understand how to apply a tool effectively.Apache 2.0
- Preview or execute content-hash syncs that reuse existing vectors for unchanged files while safely reconciling added, modified, or deleted documents.MITDestructive
- Analyze search interest over time, related topics, and queries for any topic using Google Trends data.MIT
- Retrieve related keyword ideas from Amazon's 'Related Searches' section. Each keyword returns search volume data.Apache 2.0
- Create a discount group in Paddle to organize and manage related discounts under a single name for campaigns, promotions, or team management.Apache 2.0
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- AlicenseNot gradedqualityCmaintenanceEnables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.69 npm1MIT
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- Convert texts into embedding vectors for semantic search, clustering, or deduplication. Saves vectors to a JSON file and returns its path; optionally returns vectors inline for batches up to 5 texts.MIT
- Disable semantic search for one keyspace while retaining stored vectors, allowing quick re-enable without rebuild. Choose drop_vectors to permanently erase vectors, such as when changing embedding models.MITDestructive
- Convert text into 4096-dimension vectors for retrieval-augmented generation or semantic search. Returns a summary of item count, dimensions, and input tokens so you can populate a vector store efficiently.MIT
- Search within related memories to find solutions in specific problem contexts using semantic scoping without embeddings.MIT
- Search within related memories using a specific memory as context root to find solutions in relevant knowledge without external leakage.MIT
- Assemble a prioritized brief for the beginning of a coding or planning session. Extracts recent decisions, active preferences, and related graph context. Read-only, call once per session before substantive work.MIT
- Retrieve reusable task memories before coding tasks. Load project-scoped memories and global lessons for implementation, debugging, migration, refactoring, configuration, investigation, or optimization.Apache 2.0
- Search all past meeting transcripts to find related history, prior commitments, or contradictory context before summarizing a new meeting.MIT
- Search saved knowledge to find specific information about files, fields, or concepts using a case-insensitive query.Apache 2.0
- Pose a question to a single AI model and get a direct answer, with no web search for real-time information.MIT
- Inspect the active embedding model profile to check model ID, vector dimensions, normalization, and provider, ensuring compatibility with stored vectors or external retrieval components.MIT
- Embed multiple document strings into vector representations using memo's internal document embedder. Use for diagnostics or external indexing to obtain identical document vectors.MIT
- Retrieve tags for a FRED release or find tags related to specified tag names. Filter by tag group, search text, or exclude tags. Returns a list of tags.MIT
- Convert text into numeric embedding vectors for RAG, semantic search, clustering, and similarity scoring. Supports multiple models and optional extra inputs.MIT
- Search indexed AI coding-agent conversation threads from multiple tools to recall past decisions, prior solutions, or earlier discussion. Supports keyword and hybrid semantic search.AGPL 3.0