Agents and IDEs
Claude Code, Codex, Cursor, OpenCode. They write and change code. AI Council runs on top of them through MCP and hooks and doesn't replace them.
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AI Council doesn't compete with AI agents. It's a memory and control layer on top of them. Below is a comparison with the tools people most often weigh it against, plus detailed write-ups on individual projects.
Claude Code, Codex, Cursor, OpenCode. They write and change code. AI Council runs on top of them through MCP and hooks and doesn't replace them.
CodeRabbit, Greptile, Qodo PR-Agent. They review a finished pull request. AI Council gives the agent your rules before it edits, then reviews branches against the same rules.
Unblocked, Augment Context Engine. They give the agent context on request. AI Council adds decisions and rules tied to the code and delivers them on its own.
Mem0, skillmem, agent-memory-mcp. Memory as notes and facts. AI Council's memory is about the code: tied to functions, split by branch, and re-checked when the code changes.
graphify, CodeGraph, Serena, Claude Context, TeaRAGs-MCP. They help the agent find where things are. AI Council builds a deeper graph and keeps knowledge and rules on top of it.
CLAUDE.md, AGENTS.md, Cursor rules. Enough for a small project. As the team grows, the file falls behind the code, and it can only advise.
| AI Council | Agents and IDEs | AI review | Context engines | Memory layers | Code graphs | CLAUDE.md | |
|---|---|---|---|---|---|---|---|
| Writes code | Through your agents: Claude Code, Codex, any MCP agent | Yes | No, suggests changes in the PR | No | No | No | No |
| Code understanding | L0–L10 graph: structure, dependencies, data layer, DDD, code smells, ISO 25010 | Reads files during the session | PR context; Greptile adds a repository graph | Semantic code index | No | Symbol and call graph | No |
| "Why" decisions | Entries tied to functions and modules; ticket breakdowns | No | Learnings from PR discussions | Unblocked pulls them from Slack, Jira, Confluence | Notes and facts | No | If someone writes them down |
| Team rules | MUST and SHOULD per entity, path and project | In the prompt or a file | Review rules per path | Not the focus | No | No | Advice, not checked |
| When it works | Before the edit, via hooks; after, via branch review | During the edit, if the agent asks | After the PR is opened | When the agent asks | On request | When the agent asks | At session start |
| Branches | Knowledge lives on branches and moves to the target after merge | Working copy | Per PR | Augment: branch-aware by default | No | Current state | File in git |
| Freshness | Re-checked when code changes; labels with a quote | — | Learns from reactions | Re-indexing; Unblocked flags conflicts | Not tracked | Code re-indexing | Manual |
| Team | One knowledge base per team, project chat by role | No | Org-wide rules | Yes | Usually personal memory | Usually single-user | Drifts between people |
| Air-gapped | Yes, with a license key (Enterprise) | Depends on the model | Enterprise only | Mostly cloud | Varies | Local | In the repository |
We compare by what each tool is for, not by version. Every product here is strong at its own job. Data as of October 2026.
You can build a demo over a weekend. Keeping it running for a team is a different job. Here's what takes the most time.
Rebuilding the graph after every commit takes hours. Recomputing only what changed without breaking the links is the most expensive part of the system.
A knowledge base that the team and agents write to goes stale fast without checks. You need to notice when the code under an entry has moved and flag the entry with a quote instead of rewriting it.
For an entry to point at a class rather than a line of text, you need parsers for nine languages (Python, PHP, TypeScript, JavaScript, Java, Kotlin, C#, C, C++) and a shared code model on top of them.
Knowledge from a parallel branch shouldn't leak into mainline work. After merge it should land in the target branch on its own, with no separate sync step.
Agents ask about rules on their own in fewer than one in four sessions. Hooks, rule batches, a queue and the KB gate make up a protocol tuned on real projects.
About 25 services: the graph, vectors, analysis orchestration, git and branch handling, the MCP server, review, the API and the UI.
Connect your repository, set a baseline, and check the effect after 4–6 weeks.