F
licenseNot graded
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
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self-inspect-mcp
Server Details
Send a thought, get one metathought that makes your agent inspect its own assumptions. Keyless.
If you are the author of this connector, you can claim ownership by verifying the domain or GitHub account it belongs to. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Uptime
- 100.0% over 41 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- ejentum/self-inspect-mcp
- GitHub Stars
- 8
- Server Listing
- self-inspect
TDQS
A4.7/5.0
Scored across 1 tool
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. |
TDQS
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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
self_inspect
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