Persistent memory and codebase intelligence for AI coding agents, indexes symbols, tracks sessions, and exposes structured project knowledge through an MCP server so agents stop re-reading files and start building on what they already know.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"agora-memory": {
"args": [
"memory-server"
],
"command": "agora-code"
}
}
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Persistent memory and context reduction for AI coding agents. Survives context window resets, new conversations, and agent restarts.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'git' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
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No known CVEs.
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Persistent memory and context reduction for AI coding agents. Survives context window resets, new conversations, and agent restarts.

Prerequisites: Python 3.10+ and pip. (Fully tested on macOS.)
Open a terminal and run:
pip install git+https://github.com/thebnbrkr/agora-code.git
Verify:
agora-code --version
macOS permission error? (common on macOS system Python) Use --user instead:
pip install --user git+https://github.com/thebnbrkr/agora-code.git
Then add the binary to your PATH — add this line to ~/.zshrc or ~/.bashrc:
export PATH="$(python3 -m site --user-base)/bin:$PATH"
Run this in a terminal outside of Claude Code — Claude Code does not need to be open. (macOS: use Terminal.app.)
Claude Code:
cd your-project
agora-code install-hooks --claude-code
This creates:
.claude/settings.json — registers all hooks with Claude Code.claude/hooks/*.sh — the hook scripts that fire automatically~/.claude/skills/agora-code/SKILL.md — enables /agora-code globally (created once, works in all repos).mcp.json — registers the memory MCP serverAlready have .claude/settings.json? Use --force:
agora-code install-hooks --claude-code --force
Cursor:
Copy the .cursor/ directory from this repo into your project root:
cp -r /path/to/agora-code/.cursor your-project/.cursor
Or clone the repo and copy:
git clone https://github.com/thebnbrkr/agora-code.git /tmp/agora-code
cp -r /tmp/agora-code/.cursor your-project/.cursor
Gemini CLI:
Same approach — copy .gemini/ into your project root:
cp -r /tmp/agora-code/.gemini your-project/.gemini
Restart your editor after setup.
Open Claude Code in your project. At the start of every session, type:
/agora-code
This loads the skill — it tells Claude when to summarize files, when to inject context, and when to save progress. Without it, Claude doesn't know these rules exist.
Your previous session context is injected automatically on session start. To see what was loaded:
agora-code inject
| When you... | agora-code automatically... |
|---|---|
| Start a session | Injects last checkpoint + relevant learnings from recent commits |
| Submit a prompt | Recalls relevant past findings, sets session goal |
| Read a file > 50 lines | Summarizes it via AST — saves 75–95% of tokens |
| Edit a file | Tracks the diff, re-indexes symbols |
Run git commit | Stores learnings derived from the commit |
| Context window compresses | Checkpoints before, re-injects after |
| End a session | Parses transcript → structured checkpoint in DB |
For editors without hook support, add to your MCP config:
{
"mcpServers": {
"agora-memory": {
"command": "agora-code",
"args": ["memory-server"]
}
}
}
Use which agora-code for the full path if your editor can't find it. Restart your editor.
(This feature is actively being worked on — behaviour may change.)
By default recall uses FTS5 keyword search — works with no setup. For semantic (fuzzy) search:
export OPENAI_API_KEY=sk-... # OpenAI text-embedding-3-small
export GEMINI_API_KEY=... # Gemini gemini-embedding-001
pip install "git+https://github.com/thebnbrkr/agora-code[local]" # offline, no API key
When an AI reads a 1000-line file it burns ~8000 tokens just for that read. agora-code intercepts every file read and serves a structured AST summary in