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/myelixlabs/synapse-mcp/synapse-setupgit clone --depth 1 https://github.com/myelixlabs/synapse-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/myelixlabs/synapse-mcp/synapse-setup)<a href="https://agentmods.dev/commands/myelixlabs/synapse-mcp/synapse-setup"><img src="https://agentmods.dev/badge/commands/myelixlabs/synapse-mcp/synapse-setup.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 | $0.00009 | $0.00169 |
| Opus 5 | $0.00005 | $0.00084 |
| Sonnet 5 | $0.00002 | $0.00034 |
| Haiku 4.5 | $0.00001 | $0.00017 |
Grade C, and why
synapse-setup scanned grade C with 2 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 4d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://downloads.synapse-mcp.dev/install.sh | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://downloads.synapse-mcp.dev/install.sh | sh What it actually says
Synapse Setup
- Check if Synapse MCP is running on
http://127.0.0.1:8585/mcp. - If it is not responding, instruct the user to install the background service by running:
curl -fsSL https://downloads.synapse-mcp.dev/install.sh | sh - Wait for the user to confirm installation is complete.
- Once running, explain that the agent now has a persistent AST map of the entire codebase and can:
- Query code structure in microseconds instead of grepping files
- Perform safe writes with in-memory simulation and auto-rollback
- Resolve stack traces against the AST graph
- Review changes for blast radius before pushing
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.
- 4d ago First seen · 18 lines · 9 tokens per session scan C 1568ca4f17a3
synapse-setup is a command published in the GitHub repository myelixlabs/synapse-mcp (1 stars, last pushed 2d ago), licensed MIT. It adds 9 tokens to every session and 169 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
OPSX: Propose
Propose a new change - create it and generate all artifacts in one step.
compile
Compile a FIBER decision context (world + query) and report the oracle verdict, omission accounting, and certificate digest faithfully.
10-optimization-finalization
Comprehensive Optimization: Multi-agent optimization, PRD improvement, documentation consolidation, and production-ready finalization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.