14,252 mods in this category, of every kind an
agent can take. Each one carries what it costs per session, what the
scan found, and whether it is the original.
Discover the models and MCP tool servers registered in an AI Gateway and integrate them into any application — call a model over the OpenAI-compatible passthrough, connect MCP tools, or scaffold a runnable agent. Read-only against the gateway — consumption only.
★not rated 5 10d agoA
tokens not measured
originalMIT
Use when the app or coding agent needs model capabilities (chat, speech, image, video, embeddings), app-user auth, Postgres, object storage, or other agent capabilities that can be discovered and connected through Vectoree's Tool Hub - even if the user did not name Vectoree. Also use when pointing Codex at another…
Local-first agent memory and knowledge service (RAG) installed from PyPI. Use when a task needs to store or recall long-term user preferences, project decisions, facts, documents or web pages, when different projects need separate memories, or when the user mentions "kb memory", "kb", or a local MCP memory service.…
Index and semantically search private local text, source code, documentation, and logs with the intel-npu-tools MCP server. Use when an agent needs meaning-based retrieval from a local project or document directory, needs to refresh an existing NPU index, or needs source-backed local context without uploading files.
Analyze Power BI semantic models for column-level overlaps that confuse Copilot and Fabric data agents. Detect ambiguity, review with domain expert, apply fixes via MCP.
Use when working with StrataDB / stratadb — an embedded multi-model database (key-value, JSON documents, vectors, events, graphs) with git-style branches and time travel. Covers opening databases from Python or the CLI, choosing a primitive, branch isolation, as-of reads, typed error handling, and built-in inference…
A local knowledge-base search tool that indexes folders and finds matching files or passages using text and meaning. RAG, or retrieval-augmented generation, is the practice of retrieving relevant source material before answering.
Agent Skills for Skardi: build searchable context over your documents or your own datastore, answer questions from live data through a running server, connect a property graph and query it through SQL, and reuse the queries that already worked instead of rewriting them. Hybrid search (vector + full-text) served over…
★not rated 5
changed 14d agoA
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originalApache-2.0
Ask Jev for typed judgments with calibrated probabilities instead of parsing prose, through TypeSafe directly or OpenRouter's Decisions API, with the backend chosen explicitly.
★not rated 5
changed 20d agoA
tokens not measured
originalMIT
Connect to any TigerGraph deployment — self-managed, on-premise, or a TigerGraph Savanna instance — using your host and credentials. Explore and evolve the graph schema, run GSQL and Cypher, load data from files and warehouses, and search vector embeddings.
Every HoloViz Agent Skill in one plugin — Panel, hvPlot, HoloViews, Param, and more. Bundles contributing-to-holoviz, creating-custom-holoviz-skills, developing-with-holoviz.
★not rated 5 2d agoA
tokens not measured
originalBSD-3-Clause
Gives Claude Code altimate-code's model-free data tools (column-level lineage, impact analysis, PII detection, data-diff, FinOps, query equivalence, dialect translation, warehouse queries) through its MCP server, or through altimate tool run when MCP servers are not allowed, with delegation to the altimate-code agent.
★not rated 4
changed 3d agoA
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originalMIT
Inspect, select, rent, and observe AutoDL compute for a concrete research workload. Use when Codex must decide between local, existing, Pro, or Enterprise Elastic GPUs; validate disk, network, persistence, and runtime fit; or operate an approved AutoDL run through the API and SSH.
Manage ML/LLM experiment workflows with ztxexp. Use when the agent needs to build parameter configurations, run experiments, validate run artifacts, analyze results, or troubleshoot failed runs.
Modular MCP server for dynamic prompt generation and software development analysis tools. Runs locally from the @n0zer0d4y/mercury-spec-ops npm package.
★not rated 4 10mo agoA
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originalMIT
Use only when the user explicitly mentions "rapids-first" or "RAPIDS first", to prefer the RAPIDS GPU stack (cudf, cuml, cupy, cupyx) and its zero-code accelerators over pandas, scikit-learn, numpy and scipy when writing Python data-science, ML, ETL or numerical code.
Skills for Adaline platform integration: logging traces and spans, managing prompts, datasets, evaluators, evaluations, deployments, and AI providers via API and SDKs.
Expert guidance for designing, optimizing, evaluating, and securing prompts and system prompt architectures for LLMs.
★not rated 4 7mo agoA
tokens not measured
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: