Honcho is a memory service for software agents that stores messages and events, builds representations of people and other entities over time, and provides session context, search results, and natural-language insights. It is for developers building agents that need persistent, changing state across conversations and projects, using a managed service, local stack, or self-hosted FastAPI server. The catalogue entries connect coding agents and MCP clients to Honcho’s memory system.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/plastic-labs/honchoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/plastic-labs/honcho/recall)<a href="https://agentmods.dev/commands/plastic-labs/honcho/recall"><img src="https://agentmods.dev/badge/commands/plastic-labs/honcho/recall/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/plastic-labs/honcho/recall"><img src="https://agentmods.dev/badge/commands/plastic-labs/honcho/recall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.00197 |
| Opus 5.5 | $0.00006 | $0.00079 |
| Sonnet 5.5 | $0.00003 | $0.00039 |
| Haiku 4.5 | $0.00002 | $0.00020 |
Grade A, and why
recall scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 20 lines · 15 tokens per session scan A 3441ce013679
recall is a command published in the GitHub repository plastic-labs/honcho (7,712 stars, last pushed today), licensed AGPL-3.0. It adds 15 tokens to every session and 197 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-21.
Other commands, from other repositories
load
Load the shared Wingman context for this project.
tl-search
Search thoughtline memories by keyword or topickey GLOB.
tour
Tour this project's memory — what's captured, where it lives, how to recall it (core-memory-kit).
dream
Run a curator pass over the memory dir. Produces a proposal artifact for /dream-apply. Default curator: rot.
start
Start a session — load context + memory and brief yourself on current state.
update
Mid-session checkpoint — save progress without ending the session.