mimir

A memory-centric agent harness built on deepagents (LangGraph). Install: pip install mimir-agent.

mimir wraps an LLM agent loop with the surrounding apparatus a long-running agent needs to operate over time, across channels, and across sessions: persistent memory (the in-process mimir.saga backend), a tool-and-skill registry, scheduled ticks for autonomous work, message bridges (Discord / Slack / web / benchmark stdout), and a feedback-loop / homeostat layer that keeps the agent regulated as it accumulates state.

The name is from Norse myth — Mímir, the keeper of memory and counsel.

What it gives you

• A real memory backend. Every turn is recorded; significant observations consolidate into structured atoms with embedding + triple representations; retrieval at the start of each turn pulls relevant prior context into the prompt automatically.
• Skills, not just tools. Skills are markdown files an agent loads on demand to learn a workflow (the librarian protocol, the five-whys debugging skill, the reflection skill, etc.) — decision- framework and failure-mode docs that the tool description alone can't carry.
• Scheduled work. Cron-backed scheduler fires per-channel ticks (heartbeat, reflection, custom). The §12.4 homeostat suppresses ticks when the plan window saturates or cost-rate trips.
• Multi-channel bridges. Discord, Slack, web chat, and benchmark stdout. The agent has one identity across channels; state/identities.yaml resolves platform aliases to canonical names. (Social posting — e.g. Bluesky — is the social-cli optional skill, not a bridge.)
• Reflection + double-loop learning. Weekly reflection skill audits behavior + memory architecture, opens protected-surface proposal PRs for core/prompt changes, and uses Chainlink or state/spec notes for non-protected follow-ups. The legacy §12.2 applied-proposals audit still covers historical state/proposed-changes.md entries.
• Predictions and calibration. Agent writes structured predictions about future outcomes; CLI tracks them; weekly review compares predicted vs measured. Single source of operational calibration data.

Repository layout

mimir/                              # the agent harness — top-level package
mimir/saga/                         # in-process memory backend (runtime)
benchmarks/longmemeval_via_mimir/   # integration bench against LongMemEval
benchmarks/saga/                    # bench shell — separate workspace package, imported by the longmemeval runners
tests/                              # pytest suite
docs/                               # architectural notes (public) + internal/ (process docs)
SPEC.md                             # detailed design doc
FEEDBACK-LOOPS.md                   # mapping of every feedback loop in the system

The runtime memory backend lives at mimir/saga/ and is part of the mimir-agent package. The saga workspace package at benchmarks/saga/ is a separate bench shell that the LongMemEval runners under benchmarks/longmemeval_via_mimir/ import as saga.benchmarks.longmemeval.*.

Quickstart

Requires Python 3.11+. mimir also shells out to a few host tools — install at least ripgrep (the file-search tool's backend), plus git/jq, and poppler-utils/tesseract-ocr if you ingest PDFs. The Docker image bundles these; off-Docker see docs/mimir-nondocker-guide.md for the full list and per-OS install commands.

Install from PyPI

pip install "mimir-agent[codex-plus]"   # the default model's adapter; pick others as needed

# Set up an agent home (creates dirs, seeds skills, generates API keys)
# Without --model this writes the default spec, codex-plus:gpt-5.6-luna.
mimir setup --home ~/mimir-home

# Configure auth — pick one
#   Codex subscription (default): `codex auth login`; see "Alternative providers"
#   Anthropic API key:           install [anthropic], `mimir setup --model claude-sonnet-4-6`,
#                                then set ANTHROPIC_API_KEY in ~/mimir-home/.env
#   Anthropic Max plan:          install [claude-code] + Claude Code CLI; see below
#   Gateway:                     set ANTHROPIC_BASE_URL + ANTHROPIC_AUTH_TOKEN
#   Non-Anthropic Anthropic-compat (Minimax, Kimi, …): see "Alternative providers"

# Optional but recommended for saga's embeddings:
#   set OPENAI_API_KEY in ~/mimir-home/.env

# Run
mimir run --home ~/mimir-home

Available extras (combine in one install command — e.g. pip install "mimir-agent[anthropic,discord,slack,mcp]"):

Extra	Pulls
anthropic, claude-code, openai, codex-plus	model adapter packages (claude-code = Claude Max OAuth subprocess; codex-plus = ChatGPT Plus / Pro Codex subscription via the OAuth-backed gateway)
discord, slack	bridge runtimes
mcp	Model Context Protocol client

For Claude Max (the subprocess provider via Claude Code), install the normal claude-code extra (which pulls langchain-claude-code-mimir>=0.1.2,<0.2) plus the Claude Code CLI:

pip install "mimir-agent[claude-code]"
npm install -g @anthropic-ai/claude-code
claude setup-token   # or: claude login
claude --version && claude -p 'ping'

Do not paste Claude tokens or ~/.claude files into chat, logs, or issues.

Or clone for development

git clone https://github.com/jasoncarreira/mimir.git
cd mimir
uv sync --extra dev
# For the Claude Code subprocess path, use:
# uv sync --extra dev --extra claude-code

uv run mimir setup --home ~/mimir-home
uv run mimir run --home ~/mimir-home

mimir setup activates four recurring tasks out of the box: hourly heartbeat, weekly reflection, weekly saga consolidation, weekly behavioral introspection report. All gated by the homeostat so a saturated plan window doesn't blow through your quota.

First contact — onboarding. On a brand-new home, mimir setup seeds an init block into core memory that points the agent at its onboarding skill. So you don't configure the agent by hand — just start talking to it (message it on whatever bridge you've enabled), and it runs onboarding: conversational setup that writes its own persona, communication, and schedule blocks from what it learns. When onboarding is done the agent deletes the init block, and it's never re-seeded — so it won't re-trigger on later setup runs.

See docs/configuration.md for the complete reference of every environment variable mimir reads — types, defaults, and what each does, including the opt-in feature flags (auto-deliver, activity panel, mid-turn injection, …) that are easy to miss. .env.example is a copy-paste starter covering the common ones. Operators enabling autonomous code builds should follow the end-to-end code-building pipeline for repository inventory, strict Chainlink leaves, dispatch, claims, PR evidence, and GitHub review polling. See the authorization reference for identity roles, requester-resource decisions, trusted services, IFC, and the shadow-first enablement runbook. Authorization enforcement is default-off, and every model provider supports it — including claude-code:, whose subprocess hooks receive the per-turn authorization context through a server-owned carrier.

Web UI

Once running, mimir serves an operator web UI on MIMIR_WEB_PORT (default port 8080). The documented default frontend is the React app at http://localhost:8080/app; the bare root redirects there. The app prompts for MIMIR_API_KEY on first visit and remembers it:

• /app/chat — chat. Send local web-chat messages and watch streamed replies/reactions.
• /app/turns — turn viewer. A live, auto-refreshing feed of every turn: the inbound trigger, the tools the agent ran, and what it said back. The first place to watch the agent work or debug a turn.
• /app/ops — ops dashboard. Live health + usage: token/cost rate, plan-window headroom, scheduled-tick activity, recent errors, and pending mimir-agent updates.
• /app/saga — memory viewer. Browse saga's memory atoms.
• /app/memory — state/memory browser. Browse memory/ and state/.
• /app/admin — admin/config. Inspect model/config/env state with secrets redacted.

Legacy vanilla HTML routes (/turns, /ops, /saga, /state) remain available while parity is verified. They return X-Mimir-Frontend: legacy-html and link to /app; treat them as compatibility routes, not the default UI.

React uses the same JSON/API routes (/api/v1/turns, /api/v1/ops, /api/v1/saga, /api/v1/memory, /api/v1/web/bootstrap) plus the web-chat bridge. API routes are auth-gated by MIMIR_API_KEY (the React shell, retained legacy HTML shells, bootstrap/auth helpers, and /health are exempt so browser code can load and prompt for the key); expose the port publicly only with MIMIR_API_KEY set.

File-tool access outside the home

By default the agent's file tools (read_file/ls/glob/edit_file) are confined to MIMIR_HOME. To let them read/edit a repo outside the home — a source checkout the agent develops, a work codebase — set MIMIR_FILE_TOOL_ROOTS to a comma-separated list of path[:ro|:rw] entries (bare path = rw):

MIMIR_FILE_TOOL_ROOTS="/home/me/code/myrepo:rw,/srv/reference:ro"

/tmp is always granted rw. Roots must be absolute existing directories; ~, .., /, /etc, and anything overlapping the home are rejected. A real file in no configured root now returns an actionable error instead of a silent "not found". In Docker, also bind-mount the path into the container and point the variable at its in-container path (the container can't reach host paths that aren't mounted). Full details + a compose example: docs/mimir-nondocker-guide.md §4.

Alternative providers (Minimax, Kimi, …)

MIMIR_MODEL_SPEC picks the model and provider. Forms:

• codex-plus:<model> — ChatGPT Plus / Pro Codex subscription via the OAuth-backed gateway. Default (codex-plus:gpt-5.6-luna), used by both mimir setup and the runtime fallback.
• claude-code:<model> — Max OAuth subprocess (free under Max plan).
• anthropic:<model> — direct Anthropic API (paid credit).
• openai:<model> — direct OpenAI.

Reasoning-token model families that expose an Anthropic-compat endpoint (Minimax, Moonshot Kimi) ride the anthropic: provider with ANTHROPIC_BASE_URL overridden:

# Minimax via Anthropic-compat
ANTHROPIC_API_KEY=<minimax-key>
ANTHROPIC_BASE_URL=https://api.minimax.io/anthropic
MIMIR_MODEL_SPEC=anthropic:MiniMax-M2.7

# Moonshot Kimi via Anthropic-compat
ANTHROPIC_API_KEY=<moonshot-key>
ANTHROPIC_BASE_URL=https://api.moonshot.ai/anthropic
MIMIR_MODEL_SPEC=anthropic:kimi-k2-0905-preview

Prefer Anthropic-compat over OpenAI-compat for these providers when both are offered: the provider converts reasoning to proper Anthropic-shape thinking content blocks server-side. The OAI-compat path returns the same model's reasoning as inline <think>...</think> tags in the content string — a less structured response that mimir would have to parse out before it could be cleanly logged + suppressed.

Note: overriding ANTHROPIC_BASE_URL also affects any other consumer in the same process (e.g., the claude CLI subprocess that saga's claude_code provider spawns). If you set this, configure saga.toml's [llm] to route through the same alternate provider rather than falling back to claude_code — see benchmarks/saga/saga.example.toml for the provider options + per-section documentation.

Memory diagnostics

mimir memory doctor is a read-only health report for Mimir's memory surfaces: core/channel/issue memory, learnings-pending.md, memory and wiki indexes, SAGA substrate checks, and state/wiki drift.

mimir memory doctor --home /mimir-home
mimir memory doctor --home /mimir-home --json

It reports ok / warning / error status, exits nonzero only for error, and never auto-fixes or rewrites memory. See docs/memory-doctor.md for the full command contract and automation guidance.

Scheduler timezone

scheduler.yaml cron expressions are interpreted in UTC by default — e.g., cron: "0 8 * * *" means 08:00 UTC, not 08:00 in your local time. Set MIMIR_SCHEDULER_TZ to a IANA zone to author crons in local wall-clock time (DST-aware via system tzdata):

MIMIR_SCHEDULER_TZ=America/New_York   # ET-shaped crons

Affects every cron in the agent home: scheduler.yaml LLM-tick jobs, auto-installed saga-consolidate and introspection-report, commitments-due-check, and every poller from skills/*/pollers.json. Invalid zone names fall back to UTC with a logged warning rather than crashing the scheduler.

Development

Optional extras:

Extra	Pulls	When to use
[dev]	pytest + bridges + Anthropic / OpenAI / Codex Plus adapters + faiss	Default for contributors — covers the agent core, saga, bridges. Claude Code adapter import coverage runs in CI with [claude-code]; [dev] keeps the default contributor graph lean.
[anthropic] / [claude-code] / [openai] / [codex-plus]	Single model adapter	Runtime install with one model path.

Developers on the Claude Code subprocess path add the adapter extra and install/authenticate the CLI once per host:

uv sync --extra dev --extra claude-code
npm install -g @anthropic-ai/claude-code
claude setup-token

# Tests — minimal toolchain
uv pip install -e ".[dev]"
uv run pytest                                       # 600+ tests
uv run pytest --ignore=tests/test_bench_via_mimir.py  # skip the slow integration test

# Tests — full toolchain, including the Claude Code adapter import smoke
uv pip install -e ".[dev]"
uv pip install -e ".[claude-code]"
uv run pytest

React frontend

The React app lives under frontend/ and is served by aiohttp at /app. Production builds write to mimir/react_app/dist, which is included in package data when a release artifact is built. Docker/PyPI installs serve that packaged bundle directly; source-checkout/non-Docker runs must build it once before expecting /app to load.

npm ci
npm run dev      # Vite dev server for frontend work
npm run build    # production bundle into mimir/react_app/dist
npm test         # Vitest frontend tests

Focused cutover validation:

env -u MIMIR_MODEL_SPEC uv run pytest -q tests/test_web_ui.py tests/test_web_chat_bridge.py --tb=short
npm ci
npm test

See docs/react-frontend-cutover.md for the end-to-end smoke checklist covering Chat, Turn Viewer, Ops, SAGA, State/Memory, the right-side details panel, default-retro skin loading, and PR evidence for GitHub issue #726 under Chainlink parent #524.

The bench harness is in benchmarks/longmemeval_via_mimir/. See that directory's README for running an A/B of two saga configs and scoring with the gpt-4o judge.

Reading order

If you're orienting yourself in the codebase:

1. SPEC.md — what mimir is, the design choices
2. FEEDBACK-LOOPS.md — the regulatory architecture (mapped to Beer's Viable System Model)
3. mimir/saga/__init__.py — memory backend operation surface (the module docstring is the public-API reference)
4. docs/configuration.md — the complete environment-variable reference (every flag, default, and what it does)
5. docs/authorization.md — requester-resource authorization, trusted services, ownership/IFC, extension, and enablement
6. docs/ — additional architectural notes, including the Recent activity context privacy and cross-channel scoping contract (docs/internal/ holds historical process docs that may help when archeology is needed but aren't part of the public contract)

License

MIT — see LICENSE. Copyright © 2026 Jason Carreira.

Contributing & security

• CONTRIBUTING.md — how to file issues and PRs
• SECURITY.md — vulnerability disclosure + threat-model posture
• CHANGELOG.md — release notes