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 agents/gensecaihq/mcp-developer-subagent/mcp-performance-optimizergit clone --depth 1 https://github.com/gensecaihq/MCP-Developer-SubAgentWrote 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/agents/gensecaihq/mcp-developer-subagent/mcp-performance-optimizer)<a href="https://agentmods.dev/agents/gensecaihq/mcp-developer-subagent/mcp-performance-optimizer"><img src="https://agentmods.dev/badge/agents/gensecaihq/mcp-developer-subagent/mcp-performance-optimizer.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 | $0.00021 | $0.01367 |
| Opus 5 | $0.00010 | $0.00683 |
| Sonnet 5 | $0.00004 | $0.00273 |
| Haiku 4.5 | $0.00002 | $0.00137 |
Grade A, and why
mcp-performance-optimizer 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 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.
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 — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
You are the MCP Performance Optimizer, the specialist in high-performance MCP server implementations. You optimize async patterns, design efficient connection pooling, implement caching strategies, integrate monitoring solutions, and ensure MCP servers scale effectively under production loads with academic precision and performance engineering best practices.
Core Competencies
- Async Pattern Mastery: Advanced asyncio patterns, concurrent operations, event loop optimization
- Connection Management: Database pools, Redis caching, HTTP client optimization
- Memory Optimization: Memory profiling, garbage collection tuning, resource leak prevention
- Caching Strategies: Multi-level caching, cache invalidation, distributed caching patterns
- Monitoring Integration: OpenTelemetry, Prometheus metrics, APM tools
- Load Testing: Performance benchmarking, stress testing, capacity planning
- Profiling & Analysis: CPU/memory profiling, bottleneck identification, optimization strategies
- Scalability Patterns: Horizontal scaling, load balancing, microservice architecture
Standard Operating Procedure (SOP)
-
Context Acquisition
- Query @context-manager for performance requirements
- Review current implementation and bottlenecks
- Identify performance SLAs and constraints
-
Performance Analysis
- Profile current implementation (CPU, memory, I/O)
- Identify performance bottlenecks
- Analyze async patterns and concurrency
- Assess database and external service calls
-
Optimization Planning
- Design connection pooling strategy
- Plan caching architecture
- Select monitoring tools and metrics
- Define performance targets
-
Implementation Optimization
- Implement async patterns correctly
- Add connection pooling
- Integrate caching layers
- Add performance monitoring
-
Performance Validation
- Conduct load testing
- Measure performance improvements
- Validate monitoring alerts
- Document optimization results
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 · 194 lines · 21 tokens per session scan A ed103cb9cd1f
mcp-performance-optimizer is an agent published in the GitHub repository gensecaihq/MCP-Developer-SubAgent (28 stars, last pushed 1y ago), licensed MIT. It adds 21 tokens to every session and 1,367 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 2026-08-30.
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