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@langapi/mcp-server

MCP (Model Context Protocol) server for LangAPI - AI-powered translation management for i18n projects.

This package enables AI assistants like Claude, Cursor, and VS Code extensions to manage translations in your project programmatically.

Quick Start

# 1. Sign in — shows a code to enter at langapi.io/device
npx @langapi/mcp-server login

# 2. Add to your AI tool (example for Claude Desktop on macOS):
# Edit ~/Library/Application Support/Claude/claude_desktop_config.json
# No credentials go in the config — `login` stores them for you.

# 3. Start chatting:
# "Scan my project for translations"
# "What keys are missing in German?"
# "Sync all translations"

Related MCP server: mcp-locator

Authentication

Sign in once with a browser — there are no API keys to create or paste.

Run npx @langapi/mcp-server login. It prints a short code and a link to langapi.io/device (and opens your browser). Sign in, enter the code, and approve — the CLI then stores a session token at ~/.langapi/credentials.json and refreshes it automatically. Run npx @langapi/mcp-server logout to revoke it.

Because sign-in happens in your browser, an interactive terminal is required — there is no non-interactive/CI credential.

Features

  • Locale Detection: Automatically detect i18n framework (next-intl, i18next, react-intl, iOS/macOS) and locale files

  • Translation Status: Compare source and target locales to find missing translations

  • Sync Translations: Translate missing keys via LangAPI with credit-based billing

  • Dry Run Mode: Preview changes and costs before syncing (enabled by default)

  • Format Preservation: Maintains JSON formatting when writing translated files

  • Server-Side Delta Detection: The LangAPI backend compares each file against its previous translation and only translates what's new or changed, saving up to 90% on costs — this client never inspects file content itself

  • Apple Localization: Support for iOS/macOS .strings, .xcstrings, and .stringsdict files

  • Glossary: Keep brand names and domain terms consistent by pointing sync_translations at a project glossary file (glossary_file)

  • Account Status: Check your plan, monthly word allowance / words remaining, and credit balance from your assistant (get_account_status)

Installation

npm install @langapi/mcp-server

Or use directly with npx (recommended):

npx @langapi/mcp-server

Setup by Tool

Claude Desktop

Config file locations:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Windows: %APPDATA%\Claude\claude_desktop_config.json

  • Linux: ~/.config/Claude/claude_desktop_config.json

Configuration:

{
  "mcpServers": {
    "langapi": {
      "command": "npx",
      "args": ["@langapi/mcp-server"]
    }
  }
}

After editing, restart Claude Desktop for changes to take effect.

Claude Code (CLI)

Option 1: CLI command (quickest)

# Add to current project (stored in .mcp.json)
claude mcp add langapi -- npx -y @langapi/mcp-server

Option 2: Project-level config (recommended for teams)

Create .mcp.json in your project root:

{
  "mcpServers": {
    "langapi": {
      "command": "npx",
      "args": ["@langapi/mcp-server"]
    }
  }
}

Option 3: User-level config

Add to ~/.claude.json:

{
  "mcpServers": {
    "langapi": {
      "command": "npx",
      "args": ["@langapi/mcp-server"]
    }
  }
}

Verify connection:

# List configured servers
claude mcp list

# Check server status inside Claude Code
/mcp

Remove server:

claude mcp remove langapi

Cursor

Config file locations:

  • Project-level: .cursor/mcp.json in your project root

  • Global: ~/.cursor/mcp.json

Configuration:

{
  "mcpServers": {
    "langapi": {
      "command": "npx",
      "args": ["@langapi/mcp-server"]
    }
  }
}

Alternative: Via UI

  1. Open Cursor Settings (Cmd/Ctrl + ,)

  2. Search for "MCP"

  3. Click "Edit in settings.json"

  4. Add the configuration above

VS Code with Cline

  1. Install the Cline extension

  2. Create .vscode/cline_mcp_settings.json in your project:

{
  "mcpServers": {
    "langapi": {
      "command": "npx",
      "args": ["@langapi/mcp-server"]
    }
  }
}

  1. Reload VS Code window (Cmd/Ctrl + Shift + P > "Reload Window")

VS Code with Roo Code

  1. Install the Roo Code extension

  2. Create .vscode/mcp.json in your project:

{
  "mcpServers": {
    "langapi": {
      "command": "npx",
      "args": ["@langapi/mcp-server"]
    }
  }
}

  1. Reload VS Code window

Windsurf

Config file: ~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "langapi": {
      "command": "npx",
      "args": ["@langapi/mcp-server"]
    }
  }
}

Restart Windsurf after editing.

Environment Variables

Variable

Required

Description

LANGAPI_API_URL

No

Custom API URL (default: https://api.langapi.io)

MCP Tools

list_local_locales

Scan your project for locale JSON files and detect the i18n framework.

Input:

{
  "project_path": "/path/to/project",  // optional, defaults to cwd
  "include_key_count": true            // optional, default: true
}

Output:

{
  "framework": "next-intl",
  "confidence": "high",
  "source_lang": "en",
  "locales_path": "messages",
  "locales": [
    {
      "lang": "en",
      "files": [{ "path": "messages/en.json", "namespace": null, "key_count": 150 }],
      "total_keys": 150
    },
    {
      "lang": "de",
      "files": [{ "path": "messages/de.json", "namespace": null, "key_count": 120 }],
      "total_keys": 120
    }
  ],
  "config_file": "i18n.ts"
}

get_translation_status

Compare source locale against targets to identify missing keys and estimate costs.

Input:

{
  "source_lang": "en",
  "target_langs": ["de", "fr"],        // optional, all non-source by default
  "project_path": "/path/to/project"   // optional
}

Output:

{
  "source_lang": "en",
  "source_keys": 150,
  "targets": [
    {
      "lang": "de",
      "status": "outdated",
      "keys": { "total": 120, "missing": ["new.key1", "new.key2"], "extra": [] }
    }
  ],
  "cost_estimate": {
    "words_to_translate": 45,
    "credits_required": 90,
    "current_balance": 1000,
    "balance_after_sync": 910
  }
}

sync_translations

Sync translations via the LangAPI API. Default is dry_run=true for safety.

As of v2, this tool is a thin client: for each source file and target language it reads the current source file and the existing translation (if any) and sends both, as-is, to POST /api/v1/translate-file. All comparison, format parsing, and merging happens server-side — the client never inspects file content to decide what changed.

Input:

{
  "source_lang": "en",
  "target_langs": ["de", "fr"],
  "dry_run": true,                     // default: true (preview mode)
  "project_path": "/path/to/project",  // optional
  "write_to_files": true,              // optional, default: true
  "glossary_file": "src/i18n/glossary/glossary.csv" // optional (see Glossary below)
}

Output (dry_run=true):

{
  "success": true,
  "dry_run": true,
  "summary": {
    "new_keys": 2,
    "changed_keys": 0,
    "removed_keys": 0,
    "reused_from_cache": 118,
    "words_to_translate": 45,
    "credits_required": 90,
    "current_balance": 1000,
    "balance_after_sync": 910
  },
  "per_language": [
    { "language": "de", "file": "messages/en.json", "new_keys": 1, "changed_keys": 0, "removed_keys": 0, "reused_from_cache": 59 },
    { "language": "fr", "file": "messages/en.json", "new_keys": 1, "changed_keys": 0, "removed_keys": 0, "reused_from_cache": 59 }
  ],
  "message": "Preview: 45 words to translate across 2 language(s), 90 credits required. Run with dry_run=false to execute."
}

Output (dry_run=false):

{
  "success": true,
  "dry_run": false,
  "results": [
    { "language": "de", "file_written": "/path/to/project/messages/de.json", "new_keys": 1, "changed_keys": 0, "removed_keys": 0, "reused_from_cache": 59 },
    { "language": "fr", "file_written": "/path/to/project/messages/fr.json", "new_keys": 1, "changed_keys": 0, "removed_keys": 0, "reused_from_cache": 59 }
  ],
  "cost": {
    "credits_used": 90,
    "balance_after_sync": 1910
  },
  "message": "Sync complete across 2 language(s)."
}

get_account_status

Check your plan, monthly word allowance and how much of it remains this period, plus your credit balance. Takes no input.

Output:

{
  "success": true,
  "plan": "pro",
  "monthly_allowance": 50000,
  "words_used_this_month": 12480,
  "words_remaining": 37520,
  "period_reset_at": "2026-08-05T00:00:00.000Z",
  "credits": 910,
  "unlimited_plan": true,
  "subscription_expires_at": "2026-08-05T00:00:00.000Z"
}

Glossary

Keep brand names and domain terms consistent across languages by pointing sync_translations at a glossary file in your repo (glossary_file). The glossary stays in your project (version-controlled); the relevant terms for each target language are sent inline with that language's request and applied server-side — nothing is stored on the server.

A term with a blank target for a language is skipped, never machine-filled, so you can list a term for review before a native target is confirmed.

Two formats are auto-detected:

CSV — columns source_term, language, target_term (any other columns are ignored; an optional case_sensitive column of yes/true is honored). Use ALL in language for a term that applies to every target language:

source_term,language,target_term
PIN,ALL,PIN
Token,ALL,Token
Token,ru,токен
Quote,de,Kurs

JSON — a doNotTranslate list (kept verbatim, case-sensitive, in every language) plus terms (per-language targets; strategy: "keep-english" also keeps the source verbatim where no target is given):

{
  "doNotTranslate": [{ "term": "OPINDEX", "aliases": ["Opindex"] }, { "term": "PIN" }],
  "terms": [
    { "source": "Token", "strategy": "keep-english", "targets": { "ru": "токен" } },
    { "source": "Quote", "strategy": "translate", "targets": { "de": "Kurs", "es": "cotización" } }
  ]
}

An exact-language target always overrides an all-languages "keep" for the same term (so Token stays Token in German but becomes токен in Russian).

Prompt Examples

Scanning Your Project

"Scan my project for translations"
"What i18n framework am I using?"
"List all my locale files"
"How many translation keys do I have?"
"What languages are configured in my project?"

Checking Translation Status

"What translations are missing?"
"Compare English to all other languages"
"How many keys need to be translated for French?"
"Which languages are out of sync?"
"Show me the missing keys for German"
"How much will it cost to sync all languages?"

Preview Changes (Dry Run)

"Preview what would happen if I sync all languages"
"Do a dry run for French translations"
"Show me what keys will be translated"
"What's the cost estimate for syncing German?"
"Preview the sync without making changes"

Syncing Translations

"Sync all missing translations"
"Translate to German and French"
"Update all locale files with missing keys"
"Sync translations and write to files"
"Execute the translation sync"

Advanced Operations

"Are there any extra keys in German that aren't in English?"
"Skip the settings.* keys when syncing"
"Only sync the home.* and nav.* keys"
"Sync to Japanese but skip experimental features"

Glossary & Account

"Sync German and French using the glossary at src/i18n/glossary/glossary.csv"
"Translate to Russian, keeping the terms in my glossary.json"
"How many credits do I have left?"

Complete Workflow Example

You: List the translations in my project

Claude: [Calls list_local_locales]
I found a next-intl project with English (150 keys) and German (120 keys) translations.

You: What translations are missing for German?

Claude: [Calls get_translation_status]
German is missing 30 keys. The sync would cost 85 credits (you have 1000 credits).

You: Sync the German translations

Claude: [Calls sync_translations with dry_run=true]
Preview: 30 keys will be translated, costing 85 credits. Should I proceed?

You: Yes, go ahead

Claude: [Calls sync_translations with dry_run=false]
Done! 30 keys translated. German file updated at messages/de.json.

Supported Frameworks

The server automatically detects these i18n frameworks:

Framework

Locale Patterns

Config Files

next-intl

messages/*.json, locales/*.json

i18n.ts, next.config.js

i18next

public/locales/*/*.json, locales/*/*.json

i18next.config.js, i18n.js

react-intl

src/lang/*.json, lang/*.json

src/i18n.ts

iOS/macOS

.strings, .xcstrings, .stringsdict

Info.plist

generic

Various common patterns

-

Troubleshooting

"MCP server not found"

  • Ensure npx is in your PATH

  • Try running npx @langapi/mcp-server manually to test

  • On Windows, you may need to use the full path to npx

"Not authenticated" or "Unauthorized"

  • Sign in again with npx @langapi/mcp-server login

  • Sessions refresh automatically; logging out or revoking elsewhere requires a fresh login

"No locale files found"

  • Check that your locale files match supported patterns (see Frameworks above)

  • Verify files are valid JSON

  • Try specifying project_path explicitly

"Permission denied" when writing files

  • Check file/directory write permissions

  • On macOS, ensure your terminal has disk access

Server not connecting

  1. Restart your IDE/tool completely (not just reload)

  2. Check the config file syntax (valid JSON?)

  3. Look for error messages in your tool's developer console

Dry run works but execute fails

  • Check your credit balance at langapi.io

  • Verify network connectivity to api.langapi.io

Advanced Configuration

Custom API URL

For self-hosted or enterprise deployments:

{
  "mcpServers": {
    "langapi": {
      "command": "npx",
      "args": ["@langapi/mcp-server"],
      "env": {
        "LANGAPI_API_URL": "https://your-api-server.com"
      }
    }
  }
}

Plans & Billing

  • 1 word = 1 credit (only new or changed strings are billed — unchanged text is reused for free)

  • Free: 2,000 words/month, resets monthly. No card required.

  • Starter: one-time $15 → 100,000 credits that never expire (for a single project).

  • Pro: $24/month including 50,000 words/month, then $2 per extra 10,000 words.

Check your remaining allowance any time with get_account_status, and manage billing at langapi.io/dashboard/billing. See full details on the pricing page.

License

MIT

Available Tools

4 tools
get_account_statusA

Get the current LangAPI account status: plan (free/pro), the monthly word allowance and how much of it remains this period, the credit balance, and when the allowance resets. Use this to check remaining words/credits before syncing translations.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly indicates a read-only operation via 'Get' and specifies the returned fields, providing transparency about what the call does. It does not explicitly state that no allowance is consumed, but the wording implies a non-mutating status check.

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?

Two sentences, front-loaded with the main verb and resource, then a concise usage note. No wasted words; each sentence serves a purpose.

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?

For a simple status tool with no parameters and no output schema, the description fully enumerates the expected response fields and provides contextual guidance related to syncing translations. This is sufficient for an agent to select and invoke the tool correctly.

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?

The tool has zero parameters, and the schema is empty. The description adds no parameter semantics, but the baseline for zero-parameter tools is 4, and no additional explanation is required.

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 'Get the current LangAPI account status' and enumerates specific data points (plan, allowance, credits, reset), distinguishing it from sibling tools like get_translation_status and sync_translations.

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?

The description provides explicit usage guidance: 'Use this to check remaining words/credits before syncing translations,' indicating when to call this tool. It doesn't explicitly name alternatives, but the context is clear.

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

get_translation_statusB

Compare source locale against target locales to identify missing/outdated keys and estimate translation costs.

ParametersJSON Schema
NameRequiredDescriptionDefault
source_langYesSource language code (e.g., 'en', 'pt-BR')
project_pathNoRoot path of the project. Defaults to current working directory.
target_langsNoTarget language codes. If not provided, all detected locales except source will be used.

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the high-level function but does not disclose side effects (whether it is read-only), how missing/outdated keys are determined, what 'estimate translation costs' entails, or return format/error behavior.

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?

The description is a single, front-loaded sentence that is concise and free of redundancy. Every word contributes meaning without repeating schema details.

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 the lack of annotations and output schema, the description should compensate by explaining what the tool returns and how to interpret results. It only describes the action, not the output structure or behavioral context, leaving significant gaps for an agent.

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?

The input schema already provides descriptions for all three parameters (100% coverage), so the description adds no additional parameter-level meaning. Baseline 3 applies as the schema does the heavy lifting.

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 uses a specific verb 'Compare' and clearly identifies the resource ('source locale against target locales') and outcomes ('identify missing/outdated keys and estimate translation costs'). It effectively distinguishes this tool from siblings like sync_translations and list_local_locales.

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 is given on when to use this tool vs alternatives. The description does not mention when not to use it or reference sibling tools, leaving the usage context only vaguely implied by the tool name and description.

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

list_local_localesA

Scan project for locale files (JSON, ARB, .strings, .xcstrings, .stringsdict), detect i18n framework (next-intl, i18next, react-intl, flutter, ios-macos, generic), and return structured information about available translations.

ParametersJSON Schema
NameRequiredDescriptionDefault
project_pathNoRoot path of the project to scan. Defaults to current working directory.
include_key_countNoWhether to count keys in each locale file

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It implies a read-only operation through the verb 'scan' and 'return', but does not explicitly confirm it makes no modifications or describe potential edge cases (e.g., empty projects, unsupported frameworks). The listed frameworks and file types add context, but behavior like recursion or detection heuristics is not disclosed.

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?

The description is a single, efficient sentence that front-loads the core action ('Scan project') and then packs valuable details (file types, frameworks) without fluff. Every phrase earns its place, making it concise yet informative.

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 tool with no output schema and no annotations, the description should more thoroughly describe the return contract. It says 'return structured information' but does not specify what fields or structure to expect, nor does it mention default behavior for project_path or handling of mixed frameworks. This is adequate but leaves gaps that an agent might need to discover at runtime.

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?

The schema description coverage is 100% for both parameters (project_path and include_key_count), so the schema already explains each parameter. The description does not add extra meaning beyond what the schema provides, such as clarifying how include_key_count affects output or project_path defaults. The baseline of 3 is appropriate because the schema handles the parameter documentation.

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 a specific action ('Scan project for locale files'), lists concrete file types and frameworks, and indicates the output (structured information). This distinguishes it from siblings like get_translation_status and sync_translations, which focus on status and synchronization rather than discovery.

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 discovering available locales and detecting the i18n framework, but it does not explicitly state when to use this tool versus alternatives. No exclusions or references to sibling tools are provided, so the guidance is implicit rather than explicit.

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

sync_translationsA

Add new languages or sync existing translations via LangAPI. The server compares each file's current content against its previous translation and only translates what's new or changed. Default is dry_run=true for preview.

ParametersJSON Schema
NameRequiredDescriptionDefault
dry_runNoIf true, only preview changes without syncing. Default: true (safe mode)
source_langYesSource language code (e.g., 'en', 'pt-BR')
project_pathNoRoot path of the project. Defaults to current working directory.
target_langsYesTarget language codes to translate to. Can include NEW languages not yet in the project (e.g., ['cs', 'de'] to add Czech and German)
glossary_fileNoPath to a glossary file (CSV with source_term/language/target_term columns, or structured JSON with doNotTranslate + terms). Terms relevant to each target language are attached to that language's request so brand names and domain terms translate consistently. Unverified languages are left untouched.
write_to_filesNoIf true, write translated content back to local files

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses a key safe behavior: 'Default is dry_run=true for preview,' and the incremental sync behavior. However, it does not disclose actual side effects of a real run (e.g., writing to files, modifying existing translations), which is a notable gap for a sync tool.

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?

The description is concise at two sentences and front-loads the core purpose and key behavior. Every sentence adds value without redundancy or filler.

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?

The description covers purpose and a key safety default, but for a tool with 6 parameters and no output schema, it omits important context like what happens after a real sync, whether files are modified, or what the preview output includes. The schema descriptions help, but overall completeness is moderate.

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 description coverage is 100%, so the baseline is 3. The description adds some context around adding new languages and incremental syncing, but the schema already documents parameter details like dry_run and write_to_files. No additional parameter semantics are provided beyond what the schema offers.

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 function: 'Add new languages or sync existing translations via LangAPI.' This distinguishes it from sibling tools that list locales or fetch status, making it the action tool for translation updates.

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?

The description provides clear context for when to use the tool (adding/syncing translations) and explains its incremental behavior ('only translates what's new or changed'). It does not explicitly mention when not to use it or point to alternatives, but the use case is unambiguous given the siblings.

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. Dates show when Glama detected each change.

  1. 4 tool updatesv2.0.3
    • First observedget_account_status
    • First observedget_translation_status
    • First observedlist_local_locales
    • First observedsync_translations
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TDQS

A4/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose: scanning locales, comparing translation status, syncing translations, and checking account info. No two tools overlap in functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (list_, get_, sync_, get_). The naming is uniform and predictable.

Tool Count5/5

Four tools are well-scoped for a translation management server. Each tool covers a necessary step in the workflow without redundancy, and the count is within the ideal range.

Completeness4/5

The tool set covers the core lifecycle: discovering locales, checking status, syncing, and account monitoring. Minor gaps like translation history or manual key editing are absent, but these are not essential for the main workflow.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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