ladder-mcp

by Arhimage

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.1.5
Disambiguation5/5
Each tool has a clearly distinct purpose: ask handles questions, code does repository edits, sessions lists/inspects, setup generates config, status provides diagnostics, tasks manages background work – no overlap.
Naming Consistency5/5
All tools follow a consistent 'kimi_<noun/verb>' pattern with lowercase and underscores. The naming is uniform and predictable.
Tool Count5/5
Six tools is well-scoped for a management MCP server covering core functionality without being excessive or sparse.
Completeness4/5
The set covers primary use cases (ask, code, sessions, setup, status, tasks). Minor gaps like a dedicated help or search tool exist but do not hinder core workflows.
Average 2.9/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states 'Generate... config entry,' which implies a write operation, but does not mention side effects, permissions, or the dual preview/write mode hinted by the 'write' parameter. The 'write' parameter schema description adds some context, but the description itself is silent on behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very brief (one sentence), but it is under-specified rather than concise. Important details about the tool's function and parameters are omitted, so the brevity does not serve the agent effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given six parameters (none required), no output schema, and no annotations, the description is critically incomplete. It does not explain what a 'Kimi-hosted MCP config entry' is, how the parameters affect the output, or what the tool returns. The agent lacks adequate information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is only 17% (one parameter documented), and the tool description adds no additional meaning or context for the six parameters. The description does not explain any of the parameters, leaving the agent to infer from parameter names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Generate the Kimi-hosted MCP config entry for Ladder_mcp,' which provides a specific verb and resource, distinguishing it from sibling tools like kimi_ask or kimi_code that focus on queries or code. However, the term 'Ladder_mcp' is ambiguous and the phrase 'MCP config entry' is not elaborated, slightly reducing clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives, nor are there any prerequisites or usage contexts mentioned. The description lacks any 'when to use' or 'when not to use' information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. 'Installation, auth, and diagnostics' does not disclose whether tool is read-only, destructive, or what side effects occur. Behavioral traits are not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise (3 words) but lacks detail. While brevity is positive, it compromises informational value. Front-loads key terms but not fully earned.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no annotations, no output schema, the description is incomplete. Does not explain return values, the nature of diagnostics, or how auth/installation are checked. Insufficient for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for all 3 parameters. The description adds minimal extra meaning beyond the schema (e.g., mentions 'diagnostics' relating to doctor subcall). Baseline score applicable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Installation, auth, and diagnostics' – a general purpose but not specific verb+resource. The name 'kimi_status' implies status checking, but description is broader. Does not clearly distinguish from siblings like kimi_setup (installation) or kimi_tasks (diagnostics?). Adequate but not precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No context on prerequisites or scenarios. Agent has to infer usage from sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It states stateless and text-only, but does not clarify authentication requirements, rate limits, side effects, or how the tool behaves when parameters like context are used (e.g., switching to verify mode). The description is insufficient for understanding the tool's full behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) and front-loads key traits, but it omits necessary detail. While there is no redundancy, the brevity comes at the cost of completeness, making it minimally adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain the purpose of several parameters (e.g., timeout_ms, include_thinking, max_output_tokens) or what the tool returns. This leaves the agent with insufficient context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 50%, and the tool's description adds no information about any parameters. Three parameters (timeout_ms, include_thinking, max_output_tokens) lack schema descriptions and are not addressed in the description. The description does not compensate for the low coverage.
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?
Description clearly states it is for 'stateless question or independent review' and emphasizes 'text only, no repo, no edits', which strongly distinguishes it from sibling tools like kimi_code (code-related) and kimi_sessions (session management). The purpose is specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives is provided. While it implies it is for stateless text queries, there is no mention of scenarios where other tools like kimi_code or kimi_tasks would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only mentions actions without disclosing side effects (e.g., cancellation being irreversible), permission requirements, or whether operations are read-only. The description is too minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: single sentence front-loads the core idea. No unnecessary words. Perfectly structured for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity, the description lacks context about what tasks are (e.g., from kimi_ask) and return format. Without output schema, it should at least hint at response structure. Incomplete for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description adds no additional semantic information beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear purpose: managing background work with specific actions (status, output, cancel). It differentiates from siblings like kimi_status (which likely handles a different type of status) but does not specify what kind of tasks, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like kimi_status or kimi_sessions. The description only lists actions without context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It only states 'list/inspect' without clarifying if it modifies data, required permissions, rate limits, or what 'inspect' entails. The read-only nature is assumed but not explicit.
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 a single, front-loaded sentence that efficiently conveys the core purpose. It is concise but could be slightly more informative without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with 3 optional parameters and no output schema, the description covers the basic purpose and source options. However, it lacks details on output format, default behavior, or error handling, which a moderately complete description would include.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already described. The description adds no new meaning beyond the schema summary (e.g., does not explain how 'limit' interacts with pagination or how 'work_dir' filtering works). Baseline 3 is appropriate.
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 explicitly states the verb 'List/inspect' and the resource 'Kimi sessions', and distinguishes among sources ('CLI catalog, ACP, or both'), making the purpose clear and distinct from siblings like 'kimi_ask' or 'kimi_code'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing sessions from specific sources but provides no guidance on when to use this tool versus siblings (e.g., 'kimi_ask') or when to avoid it. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must cover behavior. It mentions the default read-only guard for edit=false and transport differences, but does not disclose potential risks of editing files, required permissions, or error conditions. Moderate transparency.
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 concise at two sentences, front-loading the core purpose. The extensive parameter descriptions are placed in the schema, keeping the main description clean. Minor reduction for not exemplifying structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 12 parameters and no output schema, the description omits crucial details like return values, error handling, and session lifecycle. The parameter descriptions are helpful but do not compensate for the lack of overall context.
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?
Schema description coverage is 67%, and the description adds meaningful context beyond the schema, such as the read-only guard behavior for 'edit' and the detailed transport comparison. Some parameters like 'detail_level' lack descriptions, but overall the description enhances understanding.
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: 'Agentic work in a repository: analyze and edit files.' This is a specific verb+resource pair and distinguishes it from siblings like kimi_ask (likely Q&A) and kimi_setup (setup).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description briefly mentions defaults but lacks explicit guidance on when to use versus alternatives. However, the transport parameter description provides some context on preferring cli vs acp, but the main description does not offer clear when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![ladder-mcp MCP server](https://glama.ai/mcp/servers/Arhimage/ladder-mcp/badges/card.svg)](https://glama.ai/mcp/servers/Arhimage/ladder-mcp)

Score Badge

Copy to your README.md:

[![ladder-mcp MCP server](https://glama.ai/mcp/servers/Arhimage/ladder-mcp/badges/score.svg)](https://glama.ai/mcp/servers/Arhimage/ladder-mcp)

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/Arhimage/ladder-mcp'

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