LumabyteCo/clarifyprompt-mcp

Highlights

Built-in platform data is now declarative YAML. The 58+ hardcoded TypeScript platform arrays move to packs/platforms/*.yaml. Adding a built-in platform = appending a YAML entry, not editing TypeScript. The TS layer becomes a runtime loader with a hardcoded fallback table — malformed YAML can never soft-brick the server.

Plus the eval harness gains multi-call fixtures (setup:), with two new fixtures covering the previously-uncovered memory pipeline.

Pass 6 — YAML platform packs

packs/platforms/
  chat.yaml      (9 platforms)
  code.yaml      (9)
  document.yaml  (8)
  image.yaml     (10)
  music.yaml     (4)
  video.yaml     (11)
  voice.yaml     (7)
  README.md      (contributor docs)

To add a new built-in platform: append an entry to the relevant category file, run npm run build, open a PR. No TS edit required.

src/engine/config/platformLoader.ts reads the YAMLs at module-load and merges with a hardcoded fallback. Per-file YAML parse failures log a single stderr line and skip; the fallback fills the affected category. Missing packs/platforms/ directory falls through cleanly.

Memory-layer eval coverage

The harness now supports a setup: [...] array of MCP tool calls before the main input. Two new fixtures use it:

• memory-pack-chunk-grounds-optimize — loads an inline knowledge pack via setup, runs optimize_prompt on a related query, asserts a memory:pack_chunk:N entry surfaces in grounding.sources. Proves the full embed → store → retrieve → curate → ground pipeline.
• memory-search-ranks-pack-by-similarity — loads a multi-section pack with one SOX-related and two unrelated sections, runs memory_search for a SOX query, asserts the top result is the SOX section. Proves vector-search ranking quality.

Plus 4 new harness check types: count_min, count_max, top_result_kind, top_result_must_contain.

Test infrastructure modernization

The integration + day2 test batteries had stale assertions hardcoding 1.3.0 / 16 tools. They now read EXPECTED_VERSION from package.json and assert presence of a tool set rather than a tool count, so future version bumps no longer break the test batteries.

Adoption materials

docs/adoption/ ships with copy/paste-ready content for the 1.5 launch:

• Show HN body, Reddit r/LocalLLaMA + r/mcp posts, 5-tweet Twitter thread
• awesome-mcp-servers PR template
• Submission specs for mcp.so, Smithery, mcp-get, PulseMCP, and the modelcontextprotocol/servers list, with a recommended week-long sequencing plan

Eval baseline (qwen2.5-coder:7b-instruct-q4_K_M, single-model)

18 passed · 2 failed · 3 skipped · 95% avg score across 23 fixtures (was 17/1/3/96% across 21 in 1.4.0).

The 2 failures:

• analyzer-creative-media — persistent known signal: 7B coder-tuned models can't reliably classify creative-media prompts. Bigger models pass it.
• grounding-claude-md-applied — transient content-text check; passes on rerun.

Multi-model matrix per evals/README.md.

Compatibility

• Same MCP tool surface as 1.4.0 — 20 tools, 1 resource. No new tools, no removed tools.
• Same env-var surface. No new required env vars.
• One new runtime dep: js-yaml (was devDep) for the platform loader. ~200 KB.
• Tarball grew +9.4 kB to ship the platform packs (137.9 kB packed total).
• All pre-1.5 tools and result shapes are unchanged. Fully back-compat.

See CHANGELOG.md for the full list.

Install

npx clarifyprompt-mcp

Or as an MCP server:

{
  "mcpServers": {
    "clarifyprompt": {
      "command": "npx",
      "args": ["-y", "clarifyprompt-mcp"],
      "env": {
        "LLM_API_URL": "http://localhost:11434/v1",
        "LLM_MODEL": "qwen2.5:7b"
      }
    }
  }
}