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MCP Chat

MCP Chat은 Anthropic API를 통해 AI 모델과 대화할 수 있는 명령줄 인터페이스 애플리케이션입니다. 이 애플리케이션은 문서 검색, 명령 기반 프롬프트, MCP(Model Control Protocol) 아키텍처를 통한 확장 가능한 도구 통합을 지원합니다.

필수 조건

  • Python 3.9+

  • Anthropic API 키

Related MCP server: MCP Chat

설정

1단계: 환경 변수 구성

  1. 프로젝트 루트에 .env 파일을 생성하거나 편집하고 다음 변수가 올바르게 설정되었는지 확인하세요:

ANTHROPIC_API_KEY=""  # Enter your Anthropic API secret key

2단계: 종속성 설치

옵션 1: uv를 사용한 설정 (권장)

uv는 빠른 Python 패키지 설치 및 해결 도구입니다.

  1. 아직 설치되지 않았다면 uv를 설치하세요:

pip install uv
  1. 가상 환경을 생성하고 활성화하세요:

uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
  1. 종속성을 설치하세요:

uv pip install -e .
  1. 프로젝트 실행

uv run main.py

옵션 2: uv 없이 설정

  1. 가상 환경을 생성하고 활성화하세요:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
  1. 종속성을 설치하세요:

pip install anthropic python-dotenv prompt-toolkit "mcp[cli]==1.8.0"
  1. 프로젝트 실행

python main.py

사용법

기본 대화

메시지를 입력하고 Enter 키를 누르면 모델과 대화할 수 있습니다.

문서 검색

@ 기호 뒤에 문서 ID를 입력하여 쿼리에 문서 내용을 포함하세요:

> Tell me about @deposition.md

명령

/ 접두사를 사용하여 MCP 서버에 정의된 명령을 실행하세요:

> /summarize deposition.md

Tab 키를 누르면 명령이 자동 완성됩니다.

개발

새 문서 추가

mcp_server.py 파일을 편집하여 docs 딕셔너리에 새 문서를 추가하세요.

MCP 기능 구현

MCP 기능을 완전히 구현하려면:

  1. mcp_server.py의 TODO를 완료하세요.

  2. mcp_client.py에서 누락된 기능을 구현하세요.

린팅 및 타입 검사

구현된 린트 또는 타입 검사는 없습니다.

Available Tools

2 tools
edit_documentA

Edit a document by replacing a string in the documents content with a new string

ParametersJSON Schema
NameRequiredDescriptionDefault
doc_idYesId of the document that will be edited
new_strYesThe new text to insert in place of the old text
old_strYesThe text to replace. Must match exactly, including whitespace

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It states that a string is replaced, but does not clarify whether all occurrences are replaced or only the first, nor does it mention that the edit is permanent/mutating, any side effects, or error conditions. This ambiguity is a significant gap for a mutation 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 a single, compact sentence with no filler or redundant restatement of the tool name. It is front-loaded with the action and resource, and every word contributes meaning.

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 simple 3-parameter tool, the description plus full schema coverage is mostly sufficient for an agent to make a call. However, the missing occurrence behavior (all vs. first match) and the absence of an output schema leave some uncertainty about the tool's actual effect and return value, making it minimally complete rather than fully contextualized.

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 covers 100% of the parameters with clear descriptions. The tool description essentially paraphrases the schema (old_str replaced by new_str) without adding new semantic meaning, such as constraints or examples. Baseline 3 is appropriate because the schema carries the burden.

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 ('Edit'), names the exact resource ('a document'), and specifies the mechanism ('replacing a string ... with a new string'). This clearly distinguishes it from the sibling read_doc_contents, which is a read operation.

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 a document's content must be modified via string replacement. However, it provides no explicit guidance about when NOT to use it or when to prefer the sibling read_doc_contents instead. The alternative is only inferable from the tool name, not the description.

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

read_doc_contentsA

Read the contents of a document and return it as a string.

ParametersJSON Schema
NameRequiredDescriptionDefault
doc_idYesId of the document to read

TDQS

A4/5.0
Behavior3/5

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 does state the output behavior ('return it as a string'), but does not mention error handling, permissions, or what happens when the document does not exist. For a simple read operation, this is adequate but not rich.

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 with no wasted words. It efficiently conveys both the operation and the return format.

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?

This is a simple tool with one parameter, full schema coverage, and no output schema. The description is largely complete for a read operation, especially since it explicitly states the return type. It could be slightly stronger with error or permission context, but nothing essential is missing for basic invocation.

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 already fully documents the only parameter, doc_id, as 'Id of the document to read', so schema coverage is 100%. The description adds no additional parameter meaning beyond the schema, matching the baseline score.

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 states a specific verb and resource: 'Read the contents of a document' and explicitly notes the return type as a string. This clearly distinguishes it from the sibling 'edit_document', which implies modification rather than reading.

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 verb 'Read' establishes a clear context for when this tool is appropriate, and its contrast with 'edit_document' implies read-only usage. However, it does not explicitly state when not to use it or name the alternative.

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 updatesv0.1.0
    • First observededit_document
    • First observedread_doc_contents

TDQS

A3.6/5.0

Scored across 2 tools

Disambiguation5/5

The two tools are clearly distinct: one reads document contents, the other edits by string replacement. No ambiguity in purpose.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern: read_doc_contents and edit_document. The naming style is uniform.

Tool Count2/5

With only two tools, the server feels extremely thin for any meaningful functionality, especially given the 'Chat' name suggests broader capabilities. The surface is too limited.

Completeness2/5

The toolset covers only read and edit operations, missing essential CRUD operations like create, delete, or list. This creates significant gaps for document management workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

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