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DevRev MCP Server

by kpsunil97
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

DevRev MCP 서버

개요

DevRev용 모델 컨텍스트 프로토콜 서버입니다. DevRev API를 사용하여 정보를 검색하고 가져오는 데 사용됩니다.

Related MCP server: Scrapeless MCP Server

도구

  • search : 제공된 쿼리와 네임스페이스를 사용하여 DevRev 검색 API를 사용하여 정보를 검색합니다.

  • get_object : ID를 사용하여 DevRev 객체에 대한 모든 정보를 가져옵니다.

구성

DevRev API 키 받기

  1. https://app.devrev.ai/signup 으로 가서 계정을 만드세요.

  2. 여기의 지침에 따라 Salesforce, Zendesk 등 기존 데이터 소스에서 데이터를 가져오세요.

  3. 여기의 지침에 따라 액세스 토큰을 생성하세요.

Claude Desktop과 함께 사용

MacOS의 경우: ~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows의 경우: %APPDATA%/Claude/claude_desktop_config.json

지엑스피1

"mcpServers": {
  "devrev": {
    "command": "uv",  
    "args": [
      "--directory",
      "Path to src/devrev_mcp directory",
      "run",
      "devrev-mcp"
    ],
    "env": {
      "DEVREV_API_KEY": "YOUR_DEVREV_API_KEY"
    }
  }
}

Available Tools

2 tools
get_objectB

Get all information about a DevRev object using its ID

ParametersJSON Schema
NameRequiredDescriptionDefault
idYes

TDQS

B3.2/5.0
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 states this is a read operation ('Get'), but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what 'all information' entails. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 purpose without any wasted words. It's appropriately sized for a simple tool, making it easy to parse and understand quickly.

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 tool's simplicity (1 parameter, no output schema, no annotations), the description is minimal. It states the basic action but lacks details on return values, error cases, or operational context. Without annotations or output schema, the description should provide more completeness for effective use, but it falls short.

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 0%, so the description must compensate. It adds meaning by specifying that the 'id' parameter is for a 'DevRev object,' which clarifies the context beyond the schema's generic string type. However, it doesn't detail format, constraints, or examples, leaving some ambiguity. With one parameter, the baseline is higher, but incomplete coverage limits the score.

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 clearly states the verb ('Get') and resource ('DevRev object') with the specific mechanism ('using its ID'). It distinguishes from the sibling 'search' tool by focusing on retrieval by ID rather than searching. However, it doesn't specify what type of information is returned beyond 'all information,' which keeps it from a perfect score.

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 when you have a specific object ID, contrasting with the 'search' sibling for broader queries. However, it lacks explicit guidance on when to use this versus alternatives, prerequisites, or exclusions, leaving usage context somewhat inferred rather than clearly stated.

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.

  1. 2 tool updatesv1.0.0
    • Addedget_object
    • Addedsearch
Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

C2.9/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: get_object retrieves a specific object by ID, while search performs a broader query-based lookup. There is no overlap or ambiguity between these operations.

Naming Consistency5/5

Both tools follow a consistent verb-based naming pattern (get_ and search), with clear, descriptive names that align well with their functions. No deviations or mixed conventions are present.

Tool Count2/5

With only two tools, the server feels severely under-scoped for a DevRev platform, which typically involves objects like issues, tickets, or users. This minimal set lacks essential CRUD operations (e.g., create, update, delete) and limits agent functionality.

Completeness1/5

The tool surface is severely incomplete for a DevRev domain, offering only retrieval and search capabilities. There are no tools for creating, updating, or deleting objects, which are fundamental operations in such systems, leading to significant gaps in agent workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

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