claude-historian-mcp

🥈Silver

claude-historian-mcp is an MCP server for searching Claude Code conversation history. It helps operations teams find past solutions, track file changes, and learn from previous interactions. It connects to Claude Code and other MCP-compatible tools.

209140Updated 1w ago

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/Vvkmnn/claude-historian-mcp.git

Works with:

Claude

Overview

About This Skill

How to Use

["Install the claude-historian-mcp server and ensure it's connected to your Claude Code environment.","Run the search command in your terminal or AI chat interface, specifying the topic (e.g., 'Django REST API authentication') and optional timeframe (e.g., 'last 3 months').","Review the structured output, focusing on files modified, key steps, and outcomes. Use the 'Files Modified' section to locate relevant code snippets.","Cross-reference the findings with your current project to identify reusable patterns or solutions.","For deeper analysis, use the claude-historian-mcp's detailed query options (e.g., filter by file type or repository) to narrow down results."]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/Vvkmnn/claude-historian-mcp

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Search my Claude Code conversation history for solutions related to [TOPIC]. Focus on interactions from the last [TIMEFRAME] where files were modified or code was generated. Extract the key steps taken, files involved, and outcomes achieved. Summarize the findings in a structured format with [FORMAT_REQUIREMENTS].

Example Output

## Search Results for 'Django REST API authentication' (Last 6 months)

### **Session 1: March 15, 2024**
**Files Modified:**
- `backend/auth/views.py` (Added JWT token validation)
- `backend/settings.py` (Configured Django REST framework authentication)

**Key Steps:**
1. Identified Django REST framework's built-in TokenAuthentication as insufficient for modern needs.
2. Integrated `djangorestframework-simplejwt` for JWT-based auth.
3. Created a custom `TokenObtainPairView` to handle refresh tokens securely.
4. Tested endpoints with Postman, achieving 95% success rate in authentication tests.

**Outcome:**
- Successfully implemented stateless authentication for mobile clients.
- Reduced API response times by 30% by eliminating session overhead.

### **Session 2: February 3, 2024**
**Files Modified:**
- `backend/middleware/auth_middleware.py` (Added custom middleware for token validation)
- `backend/tests/test_auth.py` (Added unit tests for token refresh logic)

**Key Steps:**
1. Debugged a CORS issue causing token refresh failures in React frontend.
2. Implemented a `JWTRefreshSerializer` to handle token rotation securely.
3. Added middleware to validate tokens on every request, reducing unauthorized access attempts by 40%.

**Outcome:**
- Resolved intermittent authentication failures in production.
- Improved security posture by enforcing token expiration checks.

### **Recommendations:**
- Reuse the `djangorestframework-simplejwt` setup from Session 1 for future Django projects.
- Consider adding rate-limiting to the `/token/refresh/` endpoint to prevent brute-force attacks.
- Document the token refresh flow in the project's `README.md` for onboarding new developers.

---
*Total sessions found: 4 | Files modified: 8 | Key learnings: 2*