Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/dinglebear-ai/dendriteWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/plugins/dinglebear-ai/dendrite/qdrant)<a href="https://agentmods.dev/plugins/dinglebear-ai/dendrite/qdrant"><img src="https://agentmods.dev/badge/plugins/dinglebear-ai/dendrite/qdrant/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/plugins/dinglebear-ai/dendrite/qdrant"><img src="https://agentmods.dev/badge/plugins/dinglebear-ai/dendrite/qdrant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
qdrant scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What it installs
The manifest is a name and a version. 1 skill travel with it, and installing the plugin installs all of them — 85 tokens a session between them. Each is measured on its own page, and each can be installed alone.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 37 lines scan A 6b1d576e9506
qdrant is a plugin published in the GitHub repository dinglebear-ai/dendrite (1 stars, last pushed 1mo ago), licensed AGPL-3.0. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other plugins, from other repositories
neo4j-skills
Agent skills for Neo4j graph database — Cypher queries, graph modeling, drivers, imports, GraphRAG, GDS, vector indexes, and Aura provisioning.
cloudflare-vectorize
Cloudflare Vectorize vector database for semantic search and RAG. Use for vector indexes, embeddings, similarity search, or encountering dimension mismatches, filter errors.
weaviate
Weaviate plugin for Claude Coding.
skardi
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…
skardi
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.
pinecone
Pinecone vector database integration for Cursor. Create and manage indexes, upsert data, and run semantic searches via the Pinecone MCP server. Build document Q&A assistants with citations, or get started fast with /pinecone-quickstart. Great for semantic search, RAG, and agentic AI apps.