reasoning-traces
This server provides a deep_reasoning tool that lets a coding agent consult a stronger external reasoning model (e.g., Claude Opus 4.8, DeepSeek R1, o3, Gemini) to get full reasoning traces for complex problems.
Deep reasoning consultation: Send a problem with relevant code, error logs, and context to a powerful reasoning model and receive its full reasoning trace plus a conclusion.
Multi-step problem solving: Tackle subtle bugs, race conditions, deadlocks, architectural trade-offs, algorithm design, and math problems.
Full chain-of-thought access: Get the reasoning model's complete thought process (raw chain-of-thought with DeepSeek R1; summarized reasoning with Anthropic/o3/Gemini models).
Cross-check and validation: Use the returned reasoning trace to guide, verify, and cross-check your own answers before presenting them.
Constraint-driven reasoning: Specify hard requirements (performance, compatibility, style) to guide the reasoning model's response.
Automatic or manual invocation: Claude Code can automatically call the tool when it detects complex reasoning tasks, or you can trigger it on demand via a
/reasoncommand.Flexible backend and model support: Choose between OpenRouter, Anthropic, or custom backends and configure the specific model via environment variables.
Configurable parameters: Adjust reasoning effort, max output tokens, and result truncation limits.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@reasoning-traces analyze this algorithm for edge case bugs"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Reasoning Traces
Give your coding agent a stronger brain to consult.
Reasoning Traces is an MCP server + Claude Code plugin. It adds a deep_reasoning tool: the agent sends a hard problem (plus the code and context it has gathered) to a stronger reasoning model, gets back the model's full reasoning trace, and uses that trace to shape and cross-check its own answer.
By default it talks to CoreThink's hosted reasoning endpoint — you only need a CoreThink API key; the reasoning model and provider are managed server-side. (Self-host / OpenRouter / Anthropic backends are also supported — see Backends.)
Install (Claude Code)
Prerequisites: uv (curl -LsSf https://astral.sh/uv/install.sh | sh) and a CoreThink API key (contact CoreThink to get one).
Export your key (add to
~/.zshrc/~/.bashrcto persist):export CORETHINK_API_KEY=ct-...In Claude Code:
/plugin marketplace add dhruv-corethink/reasoning-traces /plugin install reasoning-traces@corethinkRestart Claude Code (or start a new session). Done — the plugin works in every project.
Verify with /mcp (the reasoning-traces server should be connected).
Related MCP server: Deepseek Thinker MCP Server
Usage
Automatic — Claude Code calls
deep_reasoningon its own when a task involves multi-step reasoning (subtle bugs, architecture trade-offs, algorithm design, math). The tool description steers this.On demand — force a consultation:
/reason why does this async queue deadlock under load?
The tool result contains the reasoning model's full trace plus its conclusion; Claude Code verifies it against your actual code before answering.
Team rollout (zero-command install)
Add this to a shared repo's .claude/settings.json and every teammate gets the plugin automatically when they trust the workspace:
{
"extraKnownMarketplaces": {
"corethink": {
"source": { "source": "github", "repo": "dhruv-corethink/reasoning-traces" }
}
},
"enabledPlugins": { "reasoning-traces@corethink": true }
}Each teammate still needs their own CORETHINK_API_KEY in their environment.
Configuration
The shipped plugin uses the corethink backend and needs only CORETHINK_API_KEY. The other variables apply when you switch backends (see Backends); set them in your shell or a per-project .env file (the server loads .env from the working directory; existing env vars win).
Variable | Default | Meaning |
| — | Required for the default ( |
| CoreThink Cloud Run URL | Override the reasoning endpoint (rarely needed) |
|
|
|
|
|
|
|
| Output cap for the reasoning call |
|
| Truncation cap on the tool result |
With the corethink backend the reasoning model is chosen server-side (Claude Opus 4.8 by default).
Other MCP clients
Any MCP client (Claude Desktop, Cursor, etc.) can run the server without the plugin:
{
"mcpServers": {
"reasoning-traces": {
"command": "uvx",
"args": ["--from", "git+https://github.com/dhruv-corethink/reasoning-traces", "reasoning-traces"],
"env": { "REASONING_BACKEND": "corethink", "CORETHINK_API_KEY": "ct-..." }
}
}
}Or with plain Claude Code CLI, no plugin:
claude mcp add --scope user reasoning-traces --env REASONING_BACKEND=corethink --env CORETHINK_API_KEY=ct-... -- uvx --from git+https://github.com/dhruv-corethink/reasoning-traces reasoning-tracesCustom backends
reasoning_traces/backends.py defines a tiny interface — reason(prompt) -> ReasoningResult(trace, conclusion). Three backends ship today (select with REASONING_BACKEND):
corethink(default) — CoreThink's hosted reasoning endpoint. Needs onlyCORETHINK_API_KEY; the upstream provider, model, and key stay server-side.openrouter— any reasoning model on OpenRouter directly (OPENROUTER_API_KEY,REASONING_MODEL).anthropic— Claude with adaptive thinking (ANTHROPIC_API_KEY; summarized reasoning — the Anthropic API never exposes raw chain of thought).
Development
git clone https://github.com/dhruv-corethink/reasoning-traces
cd reasoning-traces
echo "OPENROUTER_API_KEY=sk-or-v1-..." > .env # gitignoredOpen Claude Code in the repo — .mcp.json runs the server straight from source via uvx. The .env is loaded by the server at startup.
License
MIT
Available Tools
1 tooldeep_reasoningA
Consult a stronger reasoning model and get its full reasoning trace.
Call this BEFORE proposing a solution whenever the task involves multi-step reasoning: subtle bugs or race conditions, architectural trade-offs, algorithm design, math, or anything where a first instinct could be wrong. Use the returned trace to guide and cross-check your own answer.
The reasoning model cannot see this conversation — pass everything it needs.
Args: problem: The question or task, stated precisely. context: Relevant code, error output, logs, or background you have gathered. Include full snippets, not paraphrases. constraints: Hard requirements the solution must satisfy (performance, compatibility, style), if any.
Inputs: problem (required), context, constraints. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 1 tool
With only one tool, there is no ambiguity. The tool's purpose is clearly defined and distinct from anything else.
The single tool uses a clear, descriptive snake_case name that is consistent within itself and standard for MCP tools.
One tool is below the typical 3-15 range but suits the narrow purpose of providing reasoning traces. It feels thin but not inappropriate.
The tool covers the core functionality of retrieving a reasoning trace with necessary parameters. Minor gaps exist, such as lacking model selection, but it is largely complete for its stated purpose.
Maintenance
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