Relace MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with descriptions that explicitly differentiate similar tools (e.g., agentic_search vs cloud_search based on query type). There is no functional overlap.
Naming Consistency3/5
Cloud operations use a consistent 'cloud_' prefix, but 'agentic_search', 'fast_apply', and 'index_status' break the pattern. Mix of verb_noun and adjective_noun styles reduces predictability.
Tool Count5/5
Seven tools is well-scoped for a code search and editing server. Each tool addresses a specific need without redundancy or excessive complexity.
Completeness3/5
Covers search (local and cloud) and file editing, but lacks tools for reading full file content, deleting files, or managing local files beyond edits. Users may need to rely on external tools for basic operations.
Average 4.7/5 across 7 of 7 tools scored. Lowest: 4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on January 21, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as destructive (destructiveHint=true). The description adds detail: 'IRREVERSIBLE' and clarifies it removes both cloud data and local sync state, adding value beyond annotations.
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: two sentences plus a warning. All information is front-loaded with the core action, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (not shown), return values are handled. The description covers the destructive nature, local state removal, and the confirm parameter. Could mention confirmation step explicitly, but overall sufficient.
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 param descriptions. The description adds no extra meaning to params beyond hinting repo_id can come from cloud_list, but does not elaborate on confirm param or provide additional syntactic details.
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 deletes a cloud repository and local sync state, with the verb 'delete' and specific resource. It distinguishes from siblings like cloud_list (for listing) and implies this is for removal.
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 advises using cloud_list to find repo IDs, providing helpful context. However, it does not explicitly state when to use this tool vs alternatives (e.g., cloud_sync) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, etc. The description adds that the tool returns file paths with line ranges and explanations, providing useful context beyond the annotations. No contradictions.
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?
Description is concise (5 sentences), front-loaded with purpose, then usage guidelines, then return format and keys. No wasted words.
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 tool with one parameter, the description covers purpose, usage, return format, and is supplemented by annotations. With an output schema present, return details are adequate.
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%, and the parameter 'query' already has a detailed description with examples in the schema. The tool description adds minimal additional meaning, so baseline of 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 clearly states the tool's purpose: 'Search codebase for code locations matching a query.' It uses a specific verb ('search') and resource ('codebase'), and distinguishes from the sibling tool 'agentic_retrieval' by noting that this tool is for queries with known identifiers.
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?
Explicitly states when to use (when you know the name or structure) and when not to (conceptual/behavioral queries), naming the alternative tool 'agentic_retrieval'. This provides clear guidance for the AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint; description adds that it returns specific fields and is admin-only, complementing without contradiction.
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?
Three sentences, front-loaded with [ADMIN], no fluff; every sentence provides value.
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?
Has output schema for returns; description covers purpose, usage, and relationship to siblings; fully adequate for this simple tool.
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?
No parameters exist and schema coverage is 100%; description adds usage context (output fields) beyond schema, meeting baseline for zero-param case.
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?
Clearly states it lists all repositories, with an admin prefix and explicit use case for cloud_clear, distinguishing from normal search/sync workflow.
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?
Explicitly states when to use (find repo_id for cloud_clear) and when not needed (normal search/sync), providing clear differentiation from siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already define read-only, idempotent, non-destructive behavior. Description adds failure modes (RELACE_API_KEY, sync state) and return structure with warnings for stale indices.
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?
8 sentences, all value-adding: purpose, prerequisite, usage guidance, failure conditions, return type, warning tip. No redundancy.
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 search tool with 2 params, annotations, and output schema, the description covers purpose, prerequisites, usage, failures, return shape, and warnings. Complete.
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 detailed descriptions for both parameters. The tool description does not add extra parameter information, so 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 clearly states it searches for code by meaning using AI embeddings, distinguishing it from agentic_search for exact identifier searches.
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?
Explicitly tells when to use (conceptual queries) and when to prefer agentic_search (exact identifiers). Also mentions prerequisite cloud_sync and failure conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and readOnlyHint=false, consistent with a mutating edit. The description adds far more: explains the merging behavior with anchor lines, truncation markers, markdown handling, and a full set of error codes with their meanings and remedies. It also documents the success response format. No contradiction with annotations.
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 longer than minimal but well-structured: core purpose first, then merge details, then error codes, then a do-not-use note. Each sentence adds value. A slight trim could be made (e.g., the truncation markers sentence could be part of anchor lines), but overall it's efficient and clear.
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 that an output schema exists (indicated by CONTEXT SIGNALS) and the input schema is fully described, this description is complete: it covers all behavioral aspects, error handling with codes, response format, and explicit exclusions. No gaps remain for an agent to misunderstand.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage for all three parameters. The description still adds substantial value: for 'path' it clarifies resolution relative to MCP_BASE_DIR or MCP Roots; for 'edit_snippet' it gives concrete examples of placeholder comments and anchor line usage; for 'instruction' it provides natural language examples. This goes well beyond the schema alone.
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 opens with 'Edit or create a file using intelligent merging,' which is a specific verb+resource pair. The sibling tools are all cloud/agentic search or index utilities, so this tool is clearly distinct as a file editing tool.
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 explicitly states when to use the tool: for new files write directly, for existing files merge with anchors. It also provides a clear do-not-use instruction: 'Do NOT use this tool to delete files or clear file contents. Use a dedicated file management tool for those operations' – directly indicating when to avoid it and naming an alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint. The description adds key behavioral details: 'never refreshes indexes', conditions for needing cloud_sync, and outlines the return structure, which goes beyond the annotations.
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 three sentences, front-loaded with the primary purpose, and every sentence provides essential information without redundancy.
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 no parameters and an output schema, the description sufficiently explains the return fields (active_backend, background_monitor) and the condition for using a sibling tool. It is complete for the tool's complexity.
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 input schema has no parameters (0 params, 100% coverage). The description adds no parameter info, which is appropriate as there are none. Baseline 4 is justified.
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 specifies the verb 'inspect', the resource 'single active indexing backend', and the mode 'read-only'. It clearly defines what the tool does and distinguishes it from siblings like 'cloud_sync'.
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 explicitly states when to use the tool ('before retrieval when you need to know whether the active backend is fresh and whether semantic hints are usable') and when not to ('never refreshes indexes') with an alternative ('run cloud_sync()').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Clearly discloses incremental default, idempotent nature (aligning with annotations), and potential destructive behavior of force+mirror, plus warnings about truncation.
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?
Structured in concise paragraphs with clear headings for advanced options, return format, and failure conditions—every sentence adds value.
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?
Thoroughly covers prerequisites, usage guidance, advanced options, return structure, and failure cases, leaving no gaps given the tool's complexity and existing annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds significant value beyond schema descriptions by explaining advanced use cases for force and mirror, including when to use each option.
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 begins with a specific verb+resource ('Upload or refresh codebase to Relace Cloud for semantic search') and distinguishes from siblings by referencing index_status and cloud_search.
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?
Explicitly states when to use (after checking index_status), when to skip (if fresh), and provides advanced scenarios for force and mirror usage with concrete examples.
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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