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lens-mcp

lens-mcp

by segentic-lab
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

lens_system

Check lens installation status, fetch the current agent guide, or update the install directory. Supports dry-run and forced updates with automatic stashing of local changes.

Instructions

Install status, self-update, and the current agent guide — lens's self-maintenance tool. action='status' (read-only): running vs on-disk version, git commit, install type, install directory, Node version, and whether an update is available. action='agents_md' (read-only): returns the CURRENT AGENTS.md so you can refresh a stale pasted copy of your operating guide. action='update': dry-run by default (commits behind + incoming changes); apply=true runs update.sh (git pull + npm ci + build + self-test) — new code loads only after the MCP server restarts, and the response says so. force=true stashes local edits. Managed installs (no .git) refuse with guidance. Note: this operates on the lens INSTALL directory, not your project (the code tools' sandbox). Returns JSON.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "lens_system"
  }
}

Input Schema

NameRequiredDescriptionDefault
applyNoFor action='update': actually run the update instead of the dry-run check (default false).
forceNoFor action='update' with apply=true: auto-stash local modifications first (recoverable via `git stash pop`).
actionNostatus = version/commit/update-check (default); update = check or apply an update; agents_md = fetch the current agent guide

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries full burden. It thoroughly discloses behavioral traits: dry-run default for update, apply and force effects, the need for server restart after update, and handling of managed installs. It also states the return format is JSON.

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 moderately long but well-structured with bullet points for actions, making it scannable. It front-loads the main purpose and then details each action. A slightly more concise style could improve, but it remains clear and efficient.

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 no output schema, the description could be more specific about the return format (e.g., fields in the JSON). However, the behaviors for each action are well-documented, and the context of 'lens install directory' is clear. The tool's complexity is moderate, so the description is mostly adequate.

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, baseline is 3. The description adds value by explaining the purpose of each action (status, update, agents_md) and clarifying parameters like apply and force (e.g., dry-run, stash). This goes beyond the schema's basic descriptions.

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 specifies the tool's role: self-maintenance for the lens system, covering install status, self-update, and agent guide retrieval. It distinguishes itself from sibling tools (all code-analysis focused) by being the only meta-tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Each action is described with clear context (e.g., status for version info, agents_md for current guide, update for checking/applying). It also notes that managed installs refuse the update, providing implicit when-not-to-use guidance. However, it doesn't explicitly state alternatives or exclude other use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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