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 agentmods add instructions/sharedmemoryai/mcp-server/claude-mdgit clone --depth 1 https://github.com/sharedmemoryai/mcp-serverWhat 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 | $0.00620 | $0.00620 |
| Opus 5 | $0.00310 | $0.00310 |
| Sonnet 5 | $0.00124 | $0.00124 |
| Haiku 4.5 | $0.00062 | $0.00062 |
Grade A, and why
mcp-server CLAUDE.md 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 2d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SharedMemory — Persistent Memory for AI Agents
You have access to SharedMemory via MCP tools. Use it to persist knowledge across sessions and recall past context.
When to Remember (Proactively)
Store these automatically, without being asked:
- Decisions: Architecture choices, technology selections, trade-off resolutions ("Chose Postgres over MongoDB because...")
- Project conventions: Coding patterns, naming rules, folder structure, test practices
- Bug fixes: Root cause, investigation path, what was tried, and the solution
- User preferences: Editor settings, formatting style, communication preferences
- Environment facts: Deployment targets, CI/CD setup, credentials locations, URLs
- Key learnings: Gotchas, non-obvious behaviors, performance findings
When to Recall (Before Acting)
Check memory before:
- Starting a new task →
querywith the task description to find relevant context - Making architectural decisions →
queryfor past decisions and conventions - Debugging →
queryfor similar past bugs and solutions - Working with a specific file/module →
get_entityfor that component - Starting a new session →
get_contextto load relevant project knowledge
Tools Available
| Tool | When to Use |
|---|---|
remember |
Store a fact, decision, preference, or learning |
query |
Search for relevant memories by meaning |
batch_remember |
Store multiple related facts at once (up to 100) |
get_entity |
Get everything known about a person, project, file, or concept |
search_entities |
Find entities by name |
get_graph |
See the full knowledge graph for a volume |
get_context |
Get a formatted context block for the current task |
get_profile |
Get the auto-generated user profile |
get_memory |
Retrieve a specific memory by ID |
delete_memory |
Delete a memory |
update_memory |
Update a memory |
feedback |
Rate a memory's relevance (positive/negative) |
list_volumes |
List available memory volumes |
list_documents |
List uploaded documents |
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.
- 2d ago First seen · 53 lines · 620 tokens per session scan A b4ad10957980
mcp-server CLAUDE.md is an instructions file published in the GitHub repository sharedmemoryai/mcp-server (1 stars, last pushed 3mo ago), licensed MIT. It adds 620 tokens to every session, about $0.0031 per session on Opus 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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