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Anselmoo

mcp-zen-of-languages

by Anselmoo
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

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

CapabilityDetails
tasks
{
  "list": {},
  "cancel": {},
  "requests": {
    "tools": {
      "call": {}
    },
    "prompts": {
      "get": {}
    },
    "resources": {
      "read": {}
    }
  }
}
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
detect_languagesB

Return supported language list for analysis.

analyze_zen_violationsC

Analyze a code snippet against zen rules with stricter request-quality guardrails and richer telemetry metadata.

generate_promptsB

Generate remediation prompts with MCP-first guidance metadata and v2 versioned prompt semantics.

analyze_repositoryB

Analyze a repository path and return per-file analysis results.

analyze_batchA

Analyse a repository path and return token-budgeted, paginated violations designed for LLM context windows. Highest-severity violations appear first. Pass the returned cursor to resume from the next page.

analyze_batch_summaryA

Return a compact project health score and top-5 hotspot files from a repository scan. Always fits within a single LLM context window. Use this before analyze_batch to decide whether full pagination is needed.

analyze_batch_autoA

Smart entry point for LLM agents: automatically decides between returning all violations at once (small repos) or paginating (large repos). Pass the returned cursor back to continue pagination if has_more is true. Prefer this over manually choosing between analyze_repository and analyze_batch.

generate_agent_tasksA

Convert zen violations into structured agent task lists for automated remediation.

check_architectural_patternsA

Return detected architectural patterns for a code snippet.

generate_reportA

Generate a markdown/json report with gap analysis and prompts.

export_rule_detector_mappingA

Generate rule-detector mapping JSON from the live registry.

get_configA

Return the current server configuration including any runtime overrides.

set_config_overrideA

Override configuration values for a specific language at runtime. Overrides persist for the session.

clear_config_overridesA

Clear all runtime configuration overrides, reverting to zen-config.yaml defaults.

onboard_projectA

Get interactive onboarding guidance for setting up zen analysis on a project. Returns recommended configuration based on project characteristics.

get_supported_languagesA

Return list of all languages with zen rules and their detector coverage.

Prompts

Interactive templates invoked by user choice

NameDescription
zen_remediation_promptGenerate a remediation prompt scaffold for violations in a language.

Resources

Contextual data attached and managed by the client

NameDescription
zen_config_resourceRead-only resource exposing current configuration and active overrides.
zen_languages_resourceRead-only resource listing language principle and detector coverage counts.

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