claude-history-mcp
MCP server that makes your Claude conversation history searchable. Export your conversations from claude.ai, ingest them into a local SQLite database with full-text search, and query them from Claude Code or Claude Desktop.
Prerequisites
- Python 3.11+
- uv
Setup
1. Export your Claude history
Go to claude.ai → Settings → Export Data. You'll receive an email with a download link containing a folder with conversations.json.
2. Clone and ingest
git clone https://github.com/fifeek0/claude-history-mcp.git
cd claude-history-mcp
# Ingest exported conversations into a local SQLite database
uv run python -m claude_history.ingest /path/to/exported/data/This creates history.db in the project root with FTS5 full-text search indexes.
3. Configure as MCP server
Claude Code
Add to ~/.claude/.mcp.json:
{
"mcpServers": {
"claude-history": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/claude-history-mcp", "python", "-m", "claude_history"]
}
}
}Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"claude-history": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/claude-history-mcp", "python", "-m", "claude_history"]
}
}
}Config file location:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
Available MCP Tools
| Tool | Description | |------|-------------| | search_history | Full-text search across all messages. Supports FTS5 syntax (AND, OR, NOT, "phrases"). Optional topic filter. | | get_conversation_messages | Get full conversation content with pagination (20 messages per page). | | list_all_topics | List topic categories with conversation and message counts. | | browse_conversations | Browse conversations by topic, sorted by date or size. | | conversation_summary | Quick overview: stats, first and last human message. |
Customizing Topic Classification
Topics are assigned by keyword matching during ingestion. Edit src/claude_history/classify.py to customize the TOPIC_RULES dictionary:
TOPIC_RULES = {
"Your Topic": ["keyword1", "keyword2", ...],
...
}After editing, re-run the ingest command to reclassify all conversations.
Re-ingesting
Running ingest again deletes the existing database and rebuilds it from scratch — safe to re-run after a fresh export or after changing classification rules.
