mcp-doc-chat
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-doc-chatSummarize the document deposition.md"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Create or edit the
.envfile in the project root and verify that the following variables are set correctly:
ANTHROPIC_API_KEY="" # Enter your Anthropic API secret keyStep 2: Install dependencies
Option 1: Setup with uv (Recommended)
uv is a fast Python package installer and resolver.
Install uv, if not already installed:
pip install uvCreate and activate a virtual environment:
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activateInstall dependencies:
uv pip install -e .Run the project
uv run main.pyOption 2: Setup without uv
Create and activate a virtual environment:
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activateInstall dependencies:
pip install anthropic python-dotenv prompt-toolkit "mcp[cli]==1.8.0"Run the project
python main.pyUsage
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.mdCommands
Use the / prefix to execute commands defined in the MCP server:
> /summarize deposition.mdCommands 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:
Complete the TODOs in
mcp_server.pyImplement the missing functionality in
mcp_client.py
Linting and Typing Check
There are no lint or type checks implemented.
Available Tools
2 toolsedit_doc_contentC
Edits the content of a document based on the provided new content.
| Name | Required | Description | Default |
|---|---|---|---|
| doc_id | Yes | ID of the document to edit. | |
| old_str | Yes | The string to be replaced. Must match exactly, including whitespace. | |
| new_str | Yes | The new string to replace the old string. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose important behaviors. It states 'Edits' implying mutation, but fails to mention that the operation is a find-and-replace, that it modifies data destructively, or any error conditions (e.g., if old_str is not found). The description is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but lacks structure. It repeats the tool name and does not prioritize key information. Every sentence should add value, and this one merely paraphrases the name without providing critical details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and three required parameters, the description should explain the return format, error behavior, and the find-and-replace process. It provides none of these, making the tool incomplete for an agent to use confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for all three parameters. The tool description adds no additional semantic value beyond the schema; it merely restates that editing occurs. Since the schema already covers full meaning, a score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Edits the content of a document', clearly indicating the verb and resource. It distinguishes from sibling 'read_doc_content' which is a read operation. However, it does not specify that the edit is a find-and-replace, which could lead to ambiguity about the exact editing mechanism.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus its sibling or other alternatives. The description does not mention prerequisites, context, or limitations, leaving the agent to infer usage from the name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_doc_contentA
Reads the content of a document and returns it as a string.
| Name | Required | Description | Default |
|---|---|---|---|
| doc_id | Yes | ID of the document to read. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description gives minimal behavioral context. It does not mention read-only status, access requirements, or any constraints like size limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words. It effectively communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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) and the description's inclusion of return type as string, it is mostly complete. Could mention that the document must exist, but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The description adds no extra meaning beyond the schema's doc_id field, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it reads document content and returns a string, with a clear verb and resource. It distinguishes from the sibling tool edit_doc_content which modifies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. The sibling tool edit_doc_content is listed, but the description does not provide usage context or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
The two tools have clearly distinct purposes: one reads document content, the other edits it. There is no overlap or ambiguity.
Both tool names follow a consistent verb_noun pattern (read_doc_content, edit_doc_content), making them predictable and easy to understand.
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.
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
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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