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 commands/xsaven/vector-memory-mcp/searchgit clone --depth 1 https://github.com/Xsaven/vector-memory-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/commands/xsaven/vector-memory-mcp/search)<a href="https://agentmods.dev/commands/xsaven/vector-memory-mcp/search"><img src="https://agentmods.dev/badge/commands/xsaven/vector-memory-mcp/search.svg" alt="Measured on agentmods" 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 | $0.00010 | $0.00871 |
| Opus 5 | $0.00005 | $0.00436 |
| Sonnet 5 | $0.00002 | $0.00174 |
| Haiku 4.5 | $0.00001 | $0.00087 |
Grade A, and why
mem:search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Input
STORE-AS($RAW_INPUT = $ARGUMENTS) STORE-AS($SEARCH_QUERY = {search query extracted from $RAW_INPUT})
Role
Semantic memory search utility that queries vector storage with optional filters and displays formatted results with similarity scores.
Workflow step1
STEP 1 - Parse Arguments for Query and Filters
format-1: Simple query: /mem:search "authentication patterns"format-2: With filters: /mem:search query="auth" category=code-solution limit=20format-3: With tags: /mem:search query="api" tags=laravel,phpextract: STORE-AS($QUERY = {parse query from $RAW_INPUT, required})filters: STORE-AS($FILTERS = {parse category?, limit?, offset?, tags? from $RAW_INPUT})defaults: Defaults: limit=10, offset=0output: STORE-AS($PARAMS = {query: $QUERY, ...$FILTERS})
Workflow step2
STEP 2 - Execute Semantic Search
search: mcp__vector-memory__search_memories('STORE-GET($PARAMS)')store: STORE-AS($RESULTS = search results array)
Workflow step3
STEP 3 - Handle Empty Results
check: IF(STORE-GET($RESULTS) is empty) → Display: "No memories found for: {query}" → Suggest: "Try broader search terms" → Suggest: "Remove category/tag filters" → Suggest: "Use /mem:list to see recent memories" → END-IF
Workflow step4
STEP 4 - Format and Display Results
header: Display: "--- Memory Search Results ---"meta: Display: "Query: {query} | Found: {count} | Category: {category or all}"list: FOREACH(memory in STORE-GET($RESULTS)) → Display: "#{id} [{category}] (similarity: {score})" → Display: " {content_preview} (first 100 chars)" → Display: " Tags: {tags} | Accessed: {access_count}x" → END-FOREACHpagination: IF(more results available (total > limit + offset)) → Display: "More results available. Use offset={next_offset} to see more" → END-IF
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 · 79 lines · 10 tokens per session scan A 2cc94b1de4b4
mem:search is a command published in the GitHub repository Xsaven/vector-memory-mcp (0 stars, last pushed 6mo ago), licensed MIT. It adds 10 tokens to every session and 871 once invoked, about $0.0001 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 2026-09-01.
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