Skip to main content
Glama
Sign In
deenesjakoruzh
mcp-doc-chat

mcp-doc-chat

by amulya-acharya
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

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: MCP Chat

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

Option 1: Setup with uv (Recommended)

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_doc_contentC

Edits the content of a document based on the provided new content.

Inputs: doc_id (required), old_str (required), new_str (required).

read_doc_contentA

Reads the content of a document and returns it as a string.

Inputs: doc_id (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.3/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools have clearly distinct purposes: one reads document content, the other edits it. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern (read_doc_content, edit_doc_content), making them predictable and easy to understand.

    Tool Count4/5

    With only two tools, the server is minimal but reasonably scoped for a chat-based document interaction context. It's slightly thin but not inappropriate.

    Completeness2/5

    The tools cover reading and editing existing documents, but lack essential operations like creating, deleting, or listing documents. This is a significant gap for a document-focused server.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

    Resources

    Related MCP Connectors

    Related MCP Servers

    • MCP Chat

      IDHaunter
      F
      license
      A
      quality
      C
      maintenance
      Enables interactive chat with AI models through the Anthropic API, supporting document retrieval, command-based prompts, and extensible tool integrations via the MCP architecture.
      2
      -