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AI Agent with Architectural Memory. Impact analysis (free), tests and code from the graph (pro).
AI Agent with Architectural Memory. Impact analysis (free), tests and code from the graph (pro).
Remote endpoints: streamable-http: https://hokmah.dev/mcp
The Hokmah MCP server acts as a proxy to a remote backend API with reasonable tool-level authentication (PRO key checking for paid features). However, there are several moderate security concerns: the PRO keys file uses a hardcoded default path that may not exist in user environments, authentication is missing from free tools that interact with user repositories, unauthenticated users can request analysis of arbitrary GitHub repos (no input validation or rate limiting visible), and error handling broadly swallows exceptions during key validation. These issues don't appear malicious, but they create authorization gaps and operational risks for a production service. Supply chain analysis found 5 known vulnerabilities in dependencies (1 critical, 3 high severity).
3 files analyzed · 11 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
AI Agent with Architectural Memory — MCP Server
Gives any AI coding agent persistent understanding of codebases via TransitionGraph, IdeaGraph, and WorldModel. Analyze impact, generate tests, write code — all from the graph.
Add to your editor's MCP config (Cursor, Claude Code, VS Code, Windsurf, Cline, JetBrains):
{
"mcpServers": {
"hokmah": {
"type": "streamable-http",
"url": "https://hokmah.dev/mcp"
}
}
}
Then ask your agent: "analyze the impact of refactoring the auth module in github.com/owner/repo"
| Tool | Tier | Description |
|---|---|---|
hokmah_analyze | FREE | Impact analysis, risk score, affected files, architectural invariants |
hokmah_connect_project | FREE | Connect a GitHub repo, build the architectural graph |
hokmah_connect_mcp | FREE | Connect an external MCP server for orchestration |
hokmah_generate_tests | PRO | Test generation from the graph (40x fewer tokens) |
hokmah_generate_code | PRO | Code generation with architectural memory |
Hokmah builds a persistent architectural graph from your codebase:
When you ask "what's the impact of changing X?", Hokmah traverses the graph instead of sending your entire codebase to an LLM. That's why analyze is free (zero LLM tokens) and generate uses 40x fewer tokens.
hokmah_analyze + hokmah_connect_project + hokmah_connect_mcp (unlimited)hokmah_generate_tests + hokmah_generate_code (BYOK — bring your own LLM key)Get a Pro key at hokmah.dev.
~/Library/Application Support/Claude/claude_desktop_config.jsonclaude mcp add hokmah --transport streamable-http --url https://hokmah.dev/mcp.vscode/mcp.json in project root~/.windsurf/mcp.jsonThe hosted server at https://hokmah.dev/mcp is the recommended way to use Hokmah. To run the server yourself against your own Hokmah backend:
pip install -r requirements.txt
cp pro_keys.example.json pro_keys.json # edit with your real PRO keys
HOKMAH_API_BASE=http://localhost:8000 python mcp_server.py
Environment variables:
HOKMAH_API_BASE — upstream Hokmah API (default http://localhost:8000)HOKMAH_MCP_PORT — port to listen on (default 8001)HOKMAH_PRO_KEYS — path to the PRO keys JSON file (default /home/vpm/mcp-server/pro_keys.json)A reference systemd unit is provided in hokmah-mcp.service.
Catalyst AI Research · Haifa, Israel
MIT
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