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.
npx skills add m0nochr0me/arca-mcp --skill arca-memorygit clone --depth 1 https://github.com/m0nochr0me/arca-mcpWrote 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/skills/m0nochr0me/arca-mcp/arca-memory)<a href="https://agentmods.dev/skills/m0nochr0me/arca-mcp/arca-memory"><img src="https://agentmods.dev/badge/skills/m0nochr0me/arca-mcp/arca-memory/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/skills/m0nochr0me/arca-mcp/arca-memory"><img src="https://agentmods.dev/badge/skills/m0nochr0me/arca-mcp/arca-memory.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 | $0.00110 | $0.01896 |
| Opus 5.5 | $0.00044 | $0.00758 |
| Sonnet 5.5 | $0.00022 | $0.00379 |
| Haiku 4.5 | $0.00011 | $0.00190 |
Grade A, and why
arca-memory 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 1mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arca Memory
Arca provides persistent, semantically searchable memory across sessions, organized into buckets within a namespace. Namespace isolation is pre-configured via the MCP connection header — no agent action required.
Tool Reference
| Tool | Signature |
|---|---|
memory_add |
(content, bucket?, connected_nodes?, relationship_types?) → {memory_id} |
memory_get |
(query, bucket?, top_k=5) → {results} |
memory_get_last |
(n=5, bucket?) → {results} — most recent by creation time |
memory_delete |
(memory_id) |
memory_clear |
(bucket?) — clears "default" if omitted |
memory_list_buckets |
() → {buckets} |
memory_connect |
(source_id, target_id, relationship_type) |
memory_disconnect |
(source_id, target_id, relationship_type?) |
memory_traverse |
(memory_id, relationship_type?, depth=1) |
For graph operations and detailed traversal patterns, read references/graph-patterns.md.
Session Lifecycle
Session Start
- Call
memory_list_bucketsto orient — see what domains have history. - Call
memory_getwith a broad context query relevant to the current task before taking any action that may depend on prior decisions. - If the task is project-specific, query that project bucket explicitly.
# Example: starting a coding session
memory_get("project goals, decisions, and constraints", bucket="project-arca-mcp")
memory_get("user preferences and workflow style", bucket="preferences")
During a Session
- Store facts immediately when they become known — do not batch to end-of-session.
- After storing a memory, capture the returned
memory_idif you intend to link it to other nodes. - Update stale facts by deleting the old memory and adding a new one (no in-place update exists).
Session End
Before ending, store:
- Decisions made and their rationale
- Current project state ("Feature X is 60% complete — auth done, UI pending")
- Any unresolved items or blockers
- User preferences expressed during the session
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 217 lines · 110 tokens per session scan A 2dc40c832a3e
arca-memory is a skill published in the GitHub repository m0nochr0me/arca-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 110 tokens to every session and 1,896 once invoked, about $0.0004 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 2026-08-31.
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