contexer 0.9.0

MCP server that captures and retrieves architectural decisions and context for Claude Code sessions

contexer.ai · Discord · Docs

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Every AI coding session starts fresh. No memory of what was decided last week. No knowledge of the constraints your team spent months establishing. No recollection of the architecture choices that took three PRs to get right.

The result: developers re-explain the same rules every session. The agent re-introduces patterns already rejected. Work gets redone. Sessions run long. Budgets overrun.

Contexer fixes this by capturing decisions as they happen and replaying them at the start of your next session. It works with Claude Code, Cursor, and Codex.

What it is, concretely: a local MCP server plus a few editor hooks. Your decisions live as plain JSON in ~/.contexer/ on your own machine — nothing about your code or decisions is sent anywhere (the only network call Contexer makes is an optional version check against PyPI, which you can turn off).

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What changes

Before Contexer: You establish "mock at the service boundary, not the DB layer" in session one. Session two, the agent is back to mocking the DB. You correct it. Session three, same thing. Every session pays the re-explanation tax, and every mistake the agent makes because it forgot costs correction turns that run sessions long.

After Contexer: That rule is stored once as a constraint. Every future session starts with it already injected. The agent never forgets it. You never say it again.

The impact compounds across a team. Shared constraints mean every engineer's agent follows the same rules, enforces the same quality standards, and stays within the same architectural boundaries — without anyone managing it manually.

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vs. CLAUDE.md, AGENTS.md, .cursorrules

CLAUDE.md, AGENTS.md, and .cursorrules are worth having. They work well for stable project context — setup notes, architecture overviews, things you know before you start working.

The gap they don't cover is decisions made during development.

You can't write a CLAUDE.md entry for a constraint you haven't established yet. The rules that matter most — the ones that emerge from real work, real mistakes, real conversations — get established mid-session and disappear when it ends. CLAUDE.md captures what you remember to write down. Contexer captures what actually happened.

	CLAUDE.md / AGENTS.md / .cursorrules	Contexer
Source	Written manually, when you think of it	Captured automatically as decisions are made
Freshness	As current as the last time someone edited the file	Updated continuously; novelty filter prevents drift
Token cost	Entire file on every prompt	Only constraints/conventions at session start; architecture fetched when relevant
New repo	Blank — you start from scratch	Bootstrap scans git history and code to infer initial decisions
Scope	One file, one repo	Per-repo decisions + global rules that follow you across every repo

Today Contexer is a personal decision store — private by default, per-user, per-machine. Team sharing is next.

Use both. CLAUDE.md is the right place for onboarding context and stable project notes. Contexer is where the decisions made during development live — automatically, without discipline to maintain a file.

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Quick start

Requires Python 3.12+ and uv. Install takes under two minutes.

# Step 1 — install
uv tool install contexer

# Step 2 — wire into your AI assistant
contexer install

contexer install auto-detects which tools are present (~/.claude → Claude Code, ~/.cursor → Cursor, ~/.codex → Codex) and wires all of them. Pass --target claude, --target cursor, --target codex, or --target all to override.

Restart your AI assistant and open any git repo. Contexer runs silently from here.

See docs/install.md for verification, update, and uninstall steps.

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Use with Cursor (1.7+)

contexer install --target cursor   # or: contexer install (auto-detects ~/.cursor)

This registers Contexer's MCP server in ~/.cursor/mcp.json and wires two Cursor hook events in ~/.cursor/hooks.json:

• sessionStart — injects your stored project rules and a usage nudge, and drops a managed always-apply rule at <repo>/.cursor/rules/contexer.mdc.
• beforeSubmitPrompt — silently captures your task and any "always / never / don't / create a rule" directives.

The managed rule file (marker-guarded, so your own rules are never touched) steers the agent to call Contexer's get_context before reading files for architecture/"why" questions, and to save rules via update_context rather than writing native .cursor/rules files.

The first time Cursor calls a Contexer tool it asks you to approve it — Contexer does not pre-approve its own MCP tools for you.

Parity note: Cursor's beforeSubmitPrompt hook cannot inject context (only allow/block) and Cursor exposes no usable compaction hook. So Contexer's per-prompt steering on Cursor rides on the session-start nudge plus the always-apply rule file, rather than Claude's per-prompt hooks. The core value — automatic session-start injection of your stored rules — works identically to Claude Code.

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Use with Codex

contexer install --target codex   # or: contexer install (auto-detects ~/.codex)

This registers Contexer's MCP server in ~/.codex/config.toml (under [mcp_servers.contexer]) and wires hooks in ~/.codex/hooks.json. The config.toml edit is surgical — only the contexer stanza is added or removed, so your existing servers, plugins, projects, and secrets are left untouched.

Codex's hooks use the same events as Claude Code (SessionStart, PostToolUse, PreCompact, PostCompact, UserPromptSubmit), so Contexer runs at full Claude parity there: automatic session-start injection, per-prompt rationale and constraint capture, post-edit reminders, and context reload after compaction all work.

The first time Codex calls a Contexer tool it asks you to approve it — Contexer does not pre-approve its own MCP tools for you.

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How it works

Contexer is wired in through two mechanisms: MCP tools the agent can call (to store and fetch decisions) and editor hooks the host runs around your session (to inject context and capture directives). You work normally; most of it is invisible.

• Session start — a hook injects your stored constraints and conventions before you type anything.
• As you work — capture is two-track. Directives you state outright ("always X", "never Y", "don't Z", "create a rule…") are auto-stored deterministically by a hook. Everything else relies on the agent noticing a decision and calling the store tool — best-effort, and it does miss things. When it does, say "store that decision" and it's captured immediately.
• "Why" questions — ask about a past decision or rationale and Contexer fetches the matching entries automatically.
• Context window limit — on Claude Code, decisions are saved before compaction and restored after, so nothing is lost. (Cursor exposes no compaction hook — see the parity note above.)
• Claude Code memory tool — if a session records decisions to Claude Code's built-in memory (~/.claude/projects/.../memory/) instead of to Contexer, those facts are imported automatically — at session start, around compaction, and on exit — so they're categorised and available to the next session. Two memory systems, one source of truth.

Deduplication is not an LLM call. Before storing, Contexer checks token overlap against existing decisions — >70% overlap is treated as a duplicate and silently dropped. It's deterministic, costs no tokens, and is why you can "over-call" store without bloating anything.

At session start, the injected block looks roughly like this:

## Project rules — apply to ALL tasks in this repo:
- [convention] Use uv, not pip, for all dependency management
- [constraint] Never commit untested code — CI blocks merges below coverage
2 architecture decision(s) stored. Call get_context before reading files
for questions about architecture, design, or rationale.

First time in a repo — the agent includes a brief offer at the top of its first response. The offer adapts to how well you know the repo, judged from its git history:

• The repo has commits from you → pick quick (one question) or full (guided setup).
• No commits from your git email (e.g. a freshly cloned project) → Contexer suggests scan: it reads the code and docs instead of asking questions you can't answer.
• Can't tell → it simply asks how well you know the repo.

Resumed sessions (Claude Code's --resume / --continue) don't repeat any of this — the context is already in the conversation. If you installed Contexer mid-project, resuming an old session makes the agent mine that conversation for decisions already made and store them, no questions asked.

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Decision types

Not all context is equal. Contexer distinguishes between what must always apply and what is only relevant sometimes — and only loads what the current task actually needs.

Type	What it captures	Loaded at session start
constraint	Rules that must always apply — "never merge untested code"	Yes — always
convention	Team or project standards — "use uv not pip", "conventional commits"	Yes — always
architecture	Structural decisions — "chose REST over GraphQL"	No — fetched when relevant
pattern	Recurring implementation approaches	No — fetched when relevant

Constraints and conventions load every session because they apply to every task. Architecture and pattern decisions cost zero tokens at session start — they are retrieved only when the work requires them.

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Cost

Contexer's cost is fixed and predictable: in our testing it injects roughly 26 tokens per rule at session start, paid only for constraints and conventions. Architecture and pattern decisions cost nothing until something actually needs them.

Pre-loaded rules	Approx. tokens at session start
5	~125
10	~250
25	~625

It's paid once per session — every later prompt in that session adds nothing, since the rules are already in context. On prompts unrelated to anything stored, Contexer skips entirely: no read, no tokens. Store lookups are sub-millisecond and run before the response is generated, so they add nothing to response time.

The point isn't token compression — it's eliminated rework across sessions. The recurring, unpredictable cost of re-explaining rules and correcting re-introduced patterns is replaced by a small, flat, session-start cost.

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Managing decisions

Everything uses natural language.

Store a decision

"store that as a constraint"
"save this as a convention: always use uv not pip"
"remember this architecture decision"

Global decisions apply across all repos — use them for commit style, branch naming, or anything that travels with you:

"store that globally as a convention"
"save this as a global constraint: always use conventional commits"

Only constraint and convention types can be stored globally. Architecture and pattern decisions are always repo-specific.

Query decisions

"show me all constraints"
"what decisions did we make about postgres?"
"show everything stored for this repo"

Update or remove

"update the uv decision — we switched back to pip"
"delete the postgres decision"
"remove all outdated constraints"

The store is plain JSON at ~/.contexer/ — edit it directly if you prefer.

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Why it stays lightweight

Contexer is a single Python MCP server with a plain JSON store. No background worker. No vector database. No port listening. No infrastructure to maintain.

This is intentional. Every piece of complexity added to a memory system is a piece of complexity that can fail, drift, or accumulate noise. Contexer stores only what matters — decisions — and keeps everything inspectable, auditable, and greppable.

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Limitations

Honest about what it does not do today:

• Personal, not team. The store is per-user, per-machine. There's no team sync yet — shared rules don't propagate between developers. (It's on the roadmap.)
• Cursor parity is partial. Cursor's beforeSubmitPrompt hook can't inject context (only allow/block) and it has no usable compaction hook, so per-prompt rationale injection and compaction save/restore are Claude Code-only. On Cursor, steering rides on the session-start nudge plus an always-apply rule file.
• Capture is best-effort. Only outright directives ("always/never/don't/create a rule") are auto-stored deterministically. Other decisions depend on the agent choosing to call the store tool, and it does miss things — hence the "store that decision" escape hatch.
• Soft storage cap. Up to 500 entries per repo; beyond that, the least-reinforced decisions are evicted. There's no automatic staleness pruning — outdated decisions stay until you remove them.
• One network call. contexer status checks PyPI for a newer version. Disable with CONTEXER_NO_UPDATE_CHECK=1. Nothing else leaves your machine.

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CLI reference

Command	Description
contexer install	Connect Contexer (auto-detects Claude Code, Cursor, and/or Codex)
contexer install --target claude|cursor|codex|all	Install for a specific tool only, or all
contexer status	Show connection status, store size, current repo; warns about corrupt config files, cleans stale temp files, and notifies when a newer version is on PyPI
contexer reinstall	Re-sync after an AI assistant update
contexer uninstall	Disconnect; context store is kept
contexer uninstall --purge	Remove everything including ~/.contexer/
contexer version	Print installed version
contexer help	Show all commands and flags

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Troubleshooting

The agent isn't storing decisions automatically. Say "store that decision" and it is captured immediately.

A decision was stored but isn't appearing. Constraints and conventions load at session start. If added mid-session, they appear from the next session onward.

A decision is outdated or wrong. Say "delete the X decision" or edit the store file directly at ~/.contexer/.

A new decision wasn't saved — looks like a duplicate. Content too similar to an existing decision is silently skipped. Rephrase to include what specifically changed.

No context appeared at session start on a new repo. The agent will offer bootstrap setup. Complete it once and all future sessions will have context.

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Contributing

Bug reports, fixes, and documentation improvements are welcome. See CONTRIBUTING.md for setup, code style, and the PR process.

Questions or ideas? Join the community on Discord.

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License

MIT — see LICENSE for full terms.

The Contexer name and logo are trademarks of Contexer.ai. The MIT license does not grant rights to use the Contexer name, logo, or brand in any way that implies official affiliation.