Schema | reasoning-traces

reasoning-traces

Overview Schema Related Servers Score Discussions

Server Configuration

Describes the environment variables required to run the server.

Name	Required	Description	Default
`REASONING_MODEL`	No	Model slug for OpenRouter or anthropic backend.	deepseek/deepseek-r1-0528
`REASONING_EFFORT`	No	Effort level: low/medium/high for openrouter, up to xhigh/max for anthropic.	high
`REASONING_BACKEND`	No	Backend to use: openrouter, anthropic, or corethink.	openrouter
`OPENROUTER_API_KEY`	Yes	Required for the default backend (OpenRouter).
`REASONING_MAX_TOKENS`	No	Output cap for the reasoning call.	32000
`REASONING_MAX_RESULT_CHARS`	No	Truncation cap on the tool result.	32000

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": false }
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`experimental`	{}

Tools

Functions exposed to the LLM to take actions

Name	Description
deep_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.

Name

Description

deep_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.

Prompts

Interactive templates invoked by user choice

Name	Description
No prompts

Resources

Contextual data attached and managed by the client

Name	Description
No resources

Server Configuration
Instructions
Capabilities
Tools
Prompts
Resources

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dhruv-corethink/reasoning-traces'

If you have feedback or need assistance with the MCP directory API, please join our Discord server