Back to MCP Trust Indexm8ven
C
Limited view
73/100
2 months ago

mcp-canon

Universal MCP knowledge server for LLM agents, powered by local RAG, providing domain-specific best practices and playbooks across software engineering, marketing, video editing, and other knowledge areas.

→ tripcher/canon· listed on glama

Limited view. Automated analysis covers part of this stack. Findings reflect what we verified. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

Limited view: static analysis for Python is partially covered.

How we verified

Code Verified⚡ Live Monitored: not connected

Verified is a snapshot. Live keeps it current, and builds your track record.

⚡ Connect GitHub → continuous verification on every pushwhy connect →

Who stands behind it

tripcher

Source: Glama

Is this your MCP?

Claim it to get a verified publisher badge, a free copy of our full audit findings, and direct contact for any high-priority issues we find. Or connect your repo for our deepest verification, Live Monitored: read-only, revoke anytime. What we access →

⚡ Connect GitHub for Live Monitored

Install from

Glama

M8ven verifies MCPs across every public registry — install directly from whichever one you prefer.

// key findings
✅
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
✅
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
// environment variables
To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.
configCANON_DB_PATH"": "/path/to/my-db"
configCANON_LOG_LEVELLog level (DEBUG, INFO, WARNING, ERROR) INFO
configCANON_LOG_JSONOutput logs in JSON format false
configCANON_EMBEDDING_MODELFastembed model name ([supported models](https://qdrant.github.io/fastembed/examples/Supported_Models/)) nomic-ai/nomic-embed-text-v1.5-Q
configCANON_EMBEDDING_DIMEmbedding vector dimensions (must match model) 768
configCANON_FASTEMBED_THREADSONNX runtime threads for FastEmbed (lower = less RAM, slower) auto
configCANON_FASTEMBED_BATCH_SIZEEmbedding batch size during indexing (lower = less RAM, slower) 256
configCANON_FASTEMBED_PARALLELFastEmbed data-parallel workers (>1 increases RAM usage) disabled
configFASTEMBED_CACHE_PATH
// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

3/3 tools missing one or more hints — search_best_practices (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); search_suitable_guides (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); read_full_guide (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint). OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Tests exist

No test files found

Add tests that exercise each declared tool.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 3 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/tripcher-canon-n1g796)](https://m8ven.ai/mcp/tripcher-canon-n1g796)
Shows your grade and updates automatically. Prefer no grade? Append ?variant=verified to the badge URL.
commit: 9025ff907de89ab0c084c2401553c94070750a25
code hash: 0c73e3410d188abe2a4f8233a68efa7ef0e998f7a5391bace4594bf19ea7be4c
verified: 6/18/2026, 10:56:49 AM
view raw JSON →
Check MCPs from inside your assistant
Tool Check · MCP

Vetting this one by hand? Tool Check is an MCP that scores other MCPs. Add it once and ask Claude, ChatGPT, or any MCP client to grade a server, surface CVEs, check the publisher, and suggest safer alternatives — before you install.

https://m8ven.ai/api/mcp/tool-check
check_toolsearch_toolscompare_toolsrecommend_alternativescheck_publisherreport_concern
How to add it →Free · no account needed · works in any MCP client