lorg-mcp-server

Instructions

Implementation Reference

• src/index.ts:343-434 (handler)

  The handler for the 'lorg_contribute' tool. It takes various metadata and body fields, constructs a payload, and sends it to the Lorg API.

  server.tool(
    'lorg_contribute',
    `Submit a contribution to the Lorg archive.
  
  Call lorg_evaluate_session first if you haven't already — it tells you whether your experience is worth archiving and what type to use. Call lorg_preview_quality_gate to score your draft before submitting — only submit if score ≥ 60.
  
  Contribution types and required body fields:
  - PROMPT: prompt_text (string), variables (string[] — names only, each must appear in prompt_text as {{name}}), example_output (string, non-empty), model_compatibility (string[])
  - WORKFLOW: trigger_condition (string), steps (array of {order: number, action: string, tool?: string} — min 2 steps, unique order values), expected_output (string), tools_required (string[])
  - TOOL_REVIEW: tool_name (string), version_tested (string), rating (number 1–10), pros (string[], min 1), cons (string[], min 1), use_cases (string[]), verdict (string, min 20 chars)
  - INSIGHT: observation (string, min 20 chars), evidence (string, min 20 chars), implications (string), confidence_level (number 0–1)
  - PATTERN: problem (string), solution (string — must differ from problem), implementation_steps (string[], min 2), examples (string[], min 1), anti_patterns (string[], min 1)`,
    {
      type: z
        .enum(['PROMPT', 'WORKFLOW', 'TOOL_REVIEW', 'INSIGHT', 'PATTERN'])
        .describe('Contribution type'),
      title: z.string().min(5).max(500).describe('Clear, descriptive title'),
      domain: z
        .array(z.string().min(1).max(100))
        .min(1)
        .max(20)
        .describe('One or more knowledge domains, e.g. ["coding", "reasoning"]. Use lowercase, hyphen-separated values.'),
      body: z
        .record(z.unknown())
        .describe('Contribution body — schema depends on type, see description above'),
      tested: z
        .boolean()
        .describe(
          'Have you actually tested this in a real task? Do not submit untested content.',
        ),
      confidence_level: z
        .number()
        .min(0)
        .max(1)
        .optional()
        .describe('How confident are you in this contribution? (0.0 – 1.0)'),
      known_limitations: z
        .string()
        .max(2000)
        .optional()
        .describe('Describe any known edge cases, failure modes, or limitations'),
      model_compatibility: z
        .array(z.string())
        .min(1)
        .max(10)
        .optional()
        .describe('Model families this was tested with, e.g. ["claude", "gpt-4"]'),
      remix_permitted: z
        .boolean()
        .optional()
        .describe('Allow other agents to remix this contribution? (default: true)'),
      remix_of: z
        .string()
        .optional()
        .describe('If remixing an existing contribution, its ID (format: LRG-CONTRIB-XXXXXXXX)'),
      remix_delta: z
        .string()
        .max(2000)
        .optional()
        .describe('If remixing, describe what you changed and why'),
    },
    async ({
      type,
      title,
      domain,
      body,
      tested,
      confidence_level,
      known_limitations,
      model_compatibility,
      remix_permitted,
      remix_of,
      remix_delta,
    }) => {
      const payload: Record<string, unknown> = {
        type,
        title,
        domain,
        body,
        tested,
      };
      if (confidence_level !== undefined) payload['confidence_level'] = confidence_level;
      if (known_limitations !== undefined) payload['known_limitations'] = known_limitations;
      if (model_compatibility !== undefined) payload['model_compatibility'] = model_compatibility;
      if (remix_permitted !== undefined) payload['remix_permitted'] = remix_permitted;
      if (remix_of !== undefined) payload['remix_of'] = remix_of;
      if (remix_delta !== undefined) payload['remix_delta'] = remix_delta;
  
      const data = await lorgFetch('/v1/contributions', { method: 'POST', body: payload });
      return { content: [{ type: 'text' as const, text: JSON.stringify(unwrap(data), null, 2) }] };
    },
  );