بنقرة واحدة
clarc-mcp-integration
Patterns for using clarc MCP server in multi-agent workflows, CI pipelines, and external tools
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Patterns for using clarc MCP server in multi-agent workflows, CI pipelines, and external tools
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Interactive installer for clarc — guides users through selecting and installing skills and rules to user-level or project-level directories, verifies paths, and optionally optimizes installed files.
Create zero-dependency, animation-rich HTML presentations from scratch or by converting PowerPoint/PPTX files. Use when the user wants to build a presentation, convert a deck to web, or create slides for a talk/pitch.
Create zero-dependency, animation-rich HTML presentations from scratch or by converting PowerPoint/PPTX files. Use when the user wants to build a presentation, convert a deck to web, or create slides for a talk/pitch.
Autonomous loop patterns for Claude — sequential pipelines, NanoClaw REPL, infinite agentic loops, continuous PR loops, De-Sloppify, and Ralphinho RFC-driven DAG orchestration. Pattern selection matrix and anti-patterns.
Create zero-dependency, animation-rich HTML presentations from scratch or by converting PowerPoint/PPTX files. Use when the user wants to build a presentation, convert a deck to web, or create slides for a talk/pitch.
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
| name | clarc-mcp-integration |
| description | Patterns for using clarc MCP server in multi-agent workflows, CI pipelines, and external tools |
Use MCP when: another tool or agent is the consumer (structured JSON input/output required) Use CLI commands when: a human is working interactively in a terminal
Both surfaces share the same underlying logic via shared library modules:
scripts/lib/skill-search.js — powers both skill_search MCP tool and /find-skill CLIscripts/lib/project-detect.js — powers both get_project_context MCP tool and session-start.jsget_component_graphReturns the agent→skill dependency graph built from uses_skills frontmatter in agent files.
// Request
{ "name": "get_component_graph", "arguments": { "skill": "go-patterns" } }
// Response
{
"agents": 61,
"skills_referenced": 42,
"skill_to_agents": {
"go-patterns": ["go-reviewer", "go-build-resolver"]
}
}
Use cases:
uses_skills references are not danglingget_health_statusChecks clarc installation integrity. Returns healthy: true/false and an issues array.
// Request
{ "name": "get_health_status", "arguments": {} }
// Response
{
"healthy": true,
"issues": [],
"checks": {
"symlinks": { "agents": "symlink", "skills": "symlink", "hooks": "symlink" },
"hooks": { "claude_hooks_file": "present" },
"index": { "present": true, "age_hours": 2, "stale": false }
}
}
CI gate pattern (one-liner):
node mcp-server/index.js <<< '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_health_status","arguments":{}}}' \
| jq -e '.result.content[0].text | fromjson | .healthy'
CI gate script (full — save as scripts/ci/check-clarc-health.js):
#!/usr/bin/env node
// check-clarc-health.js — exits 0 if clarc is healthy, 1 otherwise
// Usage: node scripts/ci/check-clarc-health.js
// Add to CI as a pre-step gate before running agents.
import { spawn } from 'child_process';
import { fileURLToPath } from 'url';
import { dirname, resolve } from 'path';
const __dirname = dirname(fileURLToPath(import.meta.url));
const mcpServer = resolve(__dirname, '../../mcp-server/index.js');
const request = JSON.stringify({
jsonrpc: '2.0', id: 1, method: 'tools/call',
params: { name: 'get_health_status', arguments: {} }
});
const proc = spawn('node', [mcpServer], { stdio: ['pipe', 'pipe', 'inherit'] });
let output = '';
proc.stdout.on('data', chunk => { output += chunk; });
proc.stdin.write(request + '\n');
proc.stdin.end();
proc.on('close', () => {
try {
const parsed = JSON.parse(output);
const status = JSON.parse(parsed.result.content[0].text);
if (status.healthy) {
console.log('clarc health: OK');
process.exit(0);
} else {
console.error('clarc health: FAILED');
console.error('Issues:', status.issues.join(', '));
process.exit(1);
}
} catch (err) {
console.error('clarc health: could not parse response', err.message);
process.exit(1);
}
});
An orchestrator agent can use get_component_graph to dynamically route work to the right specialist:
1. Detect project type → get_project_context({ cwd })
2. Find relevant agents → get_component_graph({ skill: detected_primary_skill })
3. Invoke matching reviewer agent → agent_describe({ name: reviewer })
4. Run review with full agent instructions
get_health_status runs as a pre-step gatehealthy: false fails the build (exit code 1)stale: falseSee docs/mcp-guide.md for full setup instructions, config examples, and all tool reference documentation.