The MCP Chat Logger server allows you to save chat histories as well-formatted Markdown files with several useful features:
Automatic Timestamps: Adds timestamps to messages for chronological tracking
Conversation ID Support: Organizes different chat sessions
Custom Save Directory: Lets you specify where chat logs are saved
Easy Integration: Configurable through cursor/cherry studio
Exports chat conversations to structured Markdown files with automatic timestamping and session organization
Click on "Deploy 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 Chat Logger save this conversation with session ID project_planning"
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 Logger is a small Model Context Protocol server that lets an AI client save a conversation as a readable Markdown file.
Exposes a save_chat_history MCP tool
Writes messages, roles, and timestamps to Markdown
Uses an optional conversation ID in the filename and document header
Stores logs locally in the chat_logs/ directory
Related MCP server: Conversation Handoff MCP
Python 3.10 or newer
An MCP-compatible client
Clone the repository and install the locked dependencies:
git clone https://github.com/AlexiFeng/MCP_Chat_Logger.git
cd MCP_Chat_Logger
uv syncStart the server over stdio:
uv run chat_logger.pyUse an absolute path to your clone. A typical MCP client configuration looks like this:
{
"mcpServers": {
"chat_logger": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/MCP_Chat_Logger",
"run",
"chat_logger.py"
]
}
}
}The outer configuration shape can differ between clients; the command and args values remain the same.
save_chat_history accepts:
Field | Type | Required | Description |
| array | Yes | Chat messages containing |
| string | No | Identifier added to the output filename and document header |
Example message list:
[
{"role": "user", "content": "Summarize this experiment."},
{"role": "assistant", "content": "Here are the main findings..."}
]Generated files are written to chat_logs/chat_<timestamp>.md, or chat_logs/chat_<conversation_id>_<timestamp>.md when an ID is supplied.
For clients supported by Smithery:
npx -y @smithery/cli install @AlexiFeng/MCP_Chat_Logger --client claudeConversation logs are written to the machine running this server. Review the content before sharing or committing generated files. The chat_logs/ directory is excluded from Git by default.
uv sync
uv run python -m compileall chat_logger.pyIssues and pull requests are welcome.
Save chat history as a Markdown file
Args:
messages: List of chat messages, each containing role and content
conversation_id: Optional conversation ID for file naming
Inputs: messages (required), conversation_id.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly distinct as it is the sole operation available.
The single tool name 'save_chat_history' follows a clear verb_noun pattern. Since there is only one tool, consistency is inherently perfect with no deviations to assess.
A single tool is too few for a server named 'MCP Chat Logger', which suggests broader logging capabilities. This minimal set feels thin and under-scoped for the implied domain of chat logging.
The tool surface is severely incomplete for a chat logger. It only saves history, lacking essential operations like retrieving, updating, deleting, or listing chat logs, which are core to logging workflows.
Save, organize, and publish AI chat outputs as Markdown or HTML pages with shareable URLs.
Portable AI memory shared across models and harnesses - plain markdown you own.
Markdown notes in folders, with files, that your AI assistant can read, write and organise.
Markdown notes in folders, with files, that your AI assistant can read, write and organise.
