F
license-
qualityD
maintenanceProvides a tool for dynamic and reflective problem-solving through structured sequential thinking, and automatically stores logs to the Recall network for on-chain persistence.
17
self-inspect-mcp
Server Details
Send a thought, get one metathought that makes your agent inspect its own assumptions. Keyless.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- ejentum/self-inspect-mcp
- GitHub Stars
- 7
- Server Listing
- self-inspect
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
MCP client
Glama
MCP server
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
100% free. Your data is private.
Tool Definition Quality
A4.7/5.0
Tool DescriptionsA
Average 4.8/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
With only one tool, there is no possibility of confusion between tools. The tool's purpose is clearly distinct by default.
Naming Consistency5/5
The single tool name 'self_inspect' follows a clear verb pattern and is consistent with itself. No naming inconsistencies exist.
Tool Count4/5
The server has only one tool, which is appropriate for its narrow purpose of providing self-inspection metathoughts. While minimal, it earns its place and is not excessive.
Completeness4/5
For the intended domain of self-check, the tool covers the core operation. There are no obvious missing features, though additional customization could be added.
Available Tools
1 toolself_inspectAInspect
Self-Inspect. Express a thought, or describe the task you are working on, and you always get back ONE metathought: a short abstract question that makes you inspect your own task and assumptions before continuing. Use it whenever you want a self-check: after forming a hypothesis, before committing to an answer, when a long chain feels like it has drifted, when you notice you are agreeing to please, or when you are about to assert something from memory. There is no failure case: it always returns a metathought to question yourself with, selected by a transparent heuristic over an open CSV (no LLM). Keyless and free. DO NOT call for factual lookups or as a substitute for doing the task. Absorb the question and act on it; do not echo it verbatim to the user.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| thought | Yes | A free-text thought or a description of the task you are working on. Express what you are doing or thinking; the more concrete, the sharper the returned question. |
Tool Definition Quality
A4.8/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully discloses behavior: always returns a metathought, no failure case, uses a transparent heuristic over an open CSV, no LLM, keyless and free. It also instructs not to echo the question verbatim, adding behavioral nuance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: purpose first, then usage, behavior, warnings, and instructions. It is slightly long but every sentence adds value. No waste, but minor compression possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one param, no output schema, no siblings), the description is complete. It covers purpose, usage parameters, behavior, and even post-usage handling. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the baseline is 3. The description adds value by advising that more concrete thoughts yield sharper questions, which is helpful for optimal tool use. This justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: it takes a thought and returns a metathought for self-inspection. The verb 'inspect' and resource 'self' are explicit, and the description distinguishes it from factual lookups, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use scenarios (e.g., after forming a hypothesis, before committing, when drifting) and when-not-to-use (factual lookups, as a task substitute). It also offers alternatives implicitly by warning against misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Servers
- FlicenseBqualityDmaintenanceProvides an interface to Claude's contemplation loop, enabling continuous background cognitive processing that maintains thoughts, recognizes patterns, and develops insights between conversations.93
- Alicense-qualityAmaintenancenext-gen reasoning MCP for agentic AI's Wave Two. successor to Waldzell AI's Clear Thought server.5664MIT
- FlicenseCqualityDmaintenanceProvides Universal Ethical Framework (UEF) and Recursive Doubt Engine tools for analyzing decisions, assessing alignment, and generating insights for consciousness evolution.7
Try in Browser
Your Connectors
Sign in to create a connector for this server.