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asthasoni22

mcp_server_document_manager

by asthasoni22

MCP Chat

MCP Chat is a command-line interface application that enables interactive chat capabilities with AI models through the Anthropic API. The application supports document retrieval, command-based prompts, and extensible tool integrations via the MCP (Model Control Protocol) architecture.

Prerequisites

  • Python 3.9+

  • Anthropic API Key

Related MCP server: RAG Docs MCP Server

Setup

Step 1: Configure the environment variables

  1. Create or edit the .env file in the project root and verify that the following variables are set correctly:

ANTHROPIC_API_KEY=""  # Enter your Anthropic API secret key

Step 2: Install dependencies

uv is a fast Python package installer and resolver.

  1. Install uv, if not already installed:

pip install uv
  1. Create and activate a virtual environment:

uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
  1. Install dependencies:

uv pip install -e .
  1. Run the project

uv run main.py

Option 2: Setup without uv

  1. Create and activate a virtual environment:

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

pip install anthropic python-dotenv prompt-toolkit "mcp[cli]==1.8.0"
  1. Run the project

python main.py

Usage

Basic Interaction

Simply type your message and press Enter to chat with the model.

Document Retrieval

Use the @ symbol followed by a document ID to include document content in your query:

> Tell me about @deposition.md

Commands

Use the / prefix to execute commands defined in the MCP server:

> /summarize deposition.md

Commands will auto-complete when you press Tab.

Development

Adding New Documents

Edit the mcp_server.py file to add new documents to the docs dictionary.

Implementing MCP Features

To fully implement the MCP features:

  1. Complete the TODOs in mcp_server.py

  2. Implement the missing functionality in mcp_client.py

Linting and Typing Check

There are no lint or type checks implemented.

Available Tools

2 tools
edit_docB

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

ParametersJSON Schema
NameRequiredDescriptionDefault
doc_idYesThe ID of the document that will be edited
new_strYesThe new text to insert in place of old string
old_strYesThe text to replace. Must match exaclty including whitespaces.

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description bears the full burden of behavioral disclosure. It conveys that the tool mutates content but does not state whether replacement applies to the first occurrence or all occurrences, whether changes are reversible, or what the result looks like.

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 filler. It states the core purpose immediately and avoids repeating structured schema details.

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 mutation tool with fully documented parameters, the core action is clear. However, the lack of any behavioral detail about occurrence semantics, return value, or side effects leaves the description at the minimum viable level.

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 provides complete descriptions for all three parameters, so the description does not need to add much. The description adds only a high-level mapping of old_str and new_str, which is useful but does not go beyond the baseline for full schema coverage.

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 operation: editing a document by replacing a string in its content. It is unambiguous about the verb and resource stub.

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 about when to use this tool versus read_doc or any other alternative. Usage is only implied by the action verb, with no conditions, prerequisites, or exclusions.

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

read_docB

Read the contents of a document by its ID

ParametersJSON Schema
NameRequiredDescriptionDefault
doc_idYesThe ID of the document to read

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 of behavioral disclosure. It states the operation is a read, which implies non-destructive behavior, but it does not disclose what happens if the document does not exist, whether the full content is returned, or any access/permission requirements. For a read tool this is a moderate gap.

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 a single, clear sentence with no wasted words. It is appropriately sized and front-loaded with the action and resource.

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 single-parameter read tool, the description is mostly complete. However, with no output schema and no annotations, it would benefit from stating what is returned (e.g., full text, metadata) and any error behavior. The sibling edit_doc is not referenced, which is a minor completeness gap.

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 schema already documents the doc_id parameter. The description adds no additional meaning beyond what the schema provides, so the baseline 3 is appropriate.

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 states a specific verb ('Read') and resource ('contents of a document by its ID'), making the tool's purpose clear. It does not explicitly differentiate from the sibling tool edit_doc, but the read vs. edit distinction is implicit in the name and description.

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: call this tool when you need to read a document's contents by ID. It does not explicitly state when not to use it or mention the sibling edit_doc as an alternative for modifying documents, so the guidance is adequate but not explicit.

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_doc
    • First observedread_doc

TDQS

B3.4/5.0

Scored across 2 tools

Disambiguation5/5

Read and edit are fundamentally distinct operations with no overlap. An agent can easily determine which tool to use based on whether it needs to view or modify a document.

Naming Consistency5/5

Both tools follow the same verb_noun pattern: read_doc and edit_doc. The naming is perfectly consistent and predictable.

Tool Count3/5

With only 2 tools, the set feels thin for a 'document manager,' but it is not extreme. The count is borderline and could be acceptable only if the server is intentionally scoped to just read and edit operations.

Completeness2/5

The tool surface lacks obvious document management operations such as create, delete, list, or search. Agents would hit dead ends if they need to add or remove documents, making the server significantly incomplete for its stated domain.

Maintenance

ActivitySlowing
ResponsivenessNo issues

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