mcpbeat

M0 Recall

coco-research/m0-recall

Read the recent M0 operational thread for a project, newest first, to pick up work started in this or another tool. Answers 'where were we' and 'what is next' before asking the user to repeat context. Local SQLite, no embeddings, no network. Triggers on: 'm0 recall', 'where were we', 'what did we do last time', 'catch me up', 'resume context', 'read the thread', 'what is next'.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
196
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/coco-research/coco --skill m0-recall

The instruction itself

7 sections, as written by the author

/m0-recall — Read the Operational Thread

The read path for M0. Returns the most recent entries for a project, newest

first, with the next_step and last_verified that were recorded when they were

still true.

Retrieval is by project, kind and recency — there is no semantic search. That is

the whole query model, and it is why this returns in milliseconds.

Quick Reference

M0="${M0_BASE_URL:-http://127.0.0.1:8787}"
M0S="$HOME/.claude/skills/m0/scripts"

# The recent thread for a project
curl -s "$M0/api/brain/thread?project=acme-web&limit=10" | python3 -m json.tool

# Just the handoffs
curl -s "$M0/api/brain/thread?project=acme-web&kind=compact_checkpoint&limit=3"

# Without a server (same store)
python3 "$M0S/m0_server.py" read --project acme-web --limit 10

If the MCP tools are wired (/m0 mcp), call m0_recall directly — it returns the

same data already formatted for reading.

Parameters

| Parameter | Default | Notes |

|-----------|---------|-------|

| project | all projects | Omit only when you genuinely want every project. |

| limit | 20 | Capped at 500. |

| kind | all kinds | step_done, compact_checkpoint, session_end, lane_dispatched, lane_result, ambient_signal. An unknown value is rejected. |

Procedure

  • Resolve the project key the same way the write path does: $M0_PROJECT, else

the repository or directory name.

  • Start broad, then narrow. limit=10 with no kind filter shows what has

been happening. If the thread is long, kind=compact_checkpoint gives the

handoffs, which is usually the fastest way to orient.

  • Read the newest entry first. It carries the freshest next_step. Older

next_step values have usually been superseded — do not act on a stale one.

  • Summarise for the user in three lines: where the work stands, what was last

verified, and what the recorded next step is. Then say what you intend to do.

  • Check source_tool and branch on the entries you rely on. An entry written

by another tool on another branch may not describe the tree you are looking at.

  • Verify before building on a claim. last_verified records what someone said

they checked, at some earlier point. If it matters now, re-run it.

Reading the response

{
  "project": "acme-web",
  "count": 2,
  "pending_sidecars": 0,
  "degraded": null,
  "entries": [ { "ts": "…", "kind": "step_done", "text": "…", "next_step": "…" } ]
}

| Signal | What it means |

|--------|---------------|

| count: 0 | Nothing recorded for that project. Check the project key before concluding the thread is empty — a typo reads as "no memory". |

| "pending": true on an entry | It is still in the sidecar spool, not yet in the store. Real, and readable, but not durable until the next drain. |

| pending_sidecars > 0 | Some writes are spooled. Run python3 "$M0S/m0_server.py" drain. |

| degraded set | The store could not be read — another process holds the lock — so the entries shown may be only the spooled ones. Say so; do not present a partial thread as complete. |

When to call this

  • At the start of a session, before asking the user what you were doing.
  • When picking up work started in another tool — the thread is shared, so a

session in one editor can read what another wrote.

  • After a context compaction, to recover the operational state rather than

re-reading the whole history.

  • Before re-doing anything expensive. The thread often already records the

result, and whether it was verified.

Limits, stated plainly

  • No semantic search, no ranking, no similarity. Recency and kind, nothing else.
  • No entity or relationship extraction, so there is no "everything about X" query.
  • No summarisation. A long thread is long; compact_checkpoint entries are the

compression, and only because someone wrote them.

  • Only what was explicitly written is there. Nothing is captured automatically

unless a hook was installed (/m0 hooks).

For semantic retrieval over a knowledge graph, the cognee bundle is the right

tool — see the comparison in systems/m0/README.md.

How to use it

Copy the folder

Take coco-research/m0-recall from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.