Sashiko MCP
MCP server that queries the Sashiko AI kernel-patch review service to find critical/high severity vulnerabilities (LPE, UAF, OOB, etc.) in reviewed patches, including overlooked AI findings.
README
Sashiko MCP
MCP server that lets an AI agent query Sashiko — an AI kernel-patch review service — and hunt for critical/high severity vulnerabilities in the reviewed patches (LPE, UAF, OOB, refcount, race conditions, etc.), including AI reviews that may have gone unnoticed.
Install / config
cd ~/MCP/Sashiko && npm install
Register in opencode (~/.config/opencode/opencode.jsonc). Use the absolute
path to your copy of the repo on that machine (replace <PATH-TO-SASHIKO>
with the actual location):
"sashiko": {
"type": "local",
"command": ["node", "<PATH-TO-Sashiko>/src/index.js"],
"enabled": true
}
Optional env: SASHIKO_BASE_URL (default http://34.149.213.196),
SASHIKO_TIMEOUT_MS (default 30000).
Tools
| Tool | Purpose |
|---|---|
sashiko_config / sashiko_lists / sashiko_stats |
service metadata |
sashiko_stats_reviews / sashiko_stats_tools |
review + tool usage stats |
sashiko_patchsets / sashiko_messages |
paged lists with q / mailing_list filters |
sashiko_patchset |
full patchset detail + AI reviews with parsed findings |
sashiko_message |
raw message + diff |
sashiko_review |
AI review + model transcript/logs |
sashiko_find_critical |
find critical/high findings across patchsets (pre-filtered scan) |
sashiko_find |
general severity/class scan (e.g. class_keyword="lpe", severity="high") |
sashiko_endpoints |
enumerate the whole API surface |
Example queries
- "Find LPE-type vulnerability reviews in applied patches"
→
sashiko_findwithclass_keyword="lpe",severity="high" - "Show me critical findings no one noticed"
→
sashiko_find_criticalseverity="critical", then compare against patchset status - "What AI reviews mention use-after-free?"
→
sashiko_findwithkeywords="use-after-free"
Notes
- Reviews are public by design; findings are parsed from
review.output. - The
findings_critical/findings_highcounts on the patchset list serve as a cheap pre-filter before fetching detail per patchset. - See
docs/api-map.mdfor the full API and finding schema.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.