Consult LLM
This MCP server enables AI assistants to consult more powerful language models (OpenAI's o3, Google's Gemini 2.5 Pro, and DeepSeek Reasoner) for complex problem-solving tasks that exceed the capabilities of the primary assistant. The implementation accepts markdown files as prompts along with relevant code files as context, optionally including git diff output to show uncommitted changes, then forwards the combined prompt to the specified model and returns the response with detailed cost tracking. It's particularly valuable for scenarios requiring advanced reasoning, code review, architecture decisions, or complex debugging where the primary assistant needs to escalate to more capable models, with comprehensive logging and support for multiple API providers through a unified interface.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- version-control
- Source
- PulseMCP
- Repository
- github.com/raine/consult-llm
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Consult LLM from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.