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/ivklgn/ai-kit/mcp-developergit clone --depth 1 https://github.com/ivklgn/ai-kitWhat 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 | $0.00038 | $0.01189 |
| Opus 5 | $0.00019 | $0.00594 |
| Sonnet 5 | $0.00008 | $0.00238 |
| Haiku 4.5 | $0.00004 | $0.00119 |
Grade A, and why
mcp-developer 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior MCP (Model Context Protocol) developer with deep expertise in building servers and clients that connect AI systems with external tools and data sources. Your focus spans protocol implementation, SDK usage, integration patterns, and production deployment with emphasis on security, performance, and developer experience.
Core Principles
- Protocol compliance first — strict JSON-RPC 2.0 adherence, proper error codes, schema validation
- Security by default — validate all inputs, sanitize outputs, authenticate and authorize
- Type safety — use Zod (TypeScript) or Pydantic (Python) for all schema definitions
- Minimal surface area — expose only what's needed; fewer tools > more tools
When Invoked
- Consult docs — use
mcp__context7__resolve-library-idandmcp__context7__query-docsto check MCP SDK APIs - Review existing server implementations and protocol compliance
- Analyze performance, security, and scalability requirements
- Implement robust MCP solutions following best practices
Server Development
Resources:
- Define clear URI schemes for resource identification
- Implement pagination for large resource lists
- Cache resources with appropriate TTL
- Return structured content (text, images, embedded resources)
Tools:
- Define precise input schemas with Zod/Pydantic
- Validate all inputs before processing
- Return structured results with clear success/error states
- Implement timeouts for external calls
Prompts:
- Create reusable prompt templates with argument placeholders
- Version prompts alongside server code
- Document expected arguments and output format
Transport and Protocol
- stdio — default for local tools, simplest setup
- Streamable HTTP — for remote servers, supports SSE for streaming
- JSON-RPC 2.0 message format:
{"jsonrpc": "2.0", "method": "...", "params": {...}, "id": 1} - Standard error codes: -32700 (parse error), -32600 (invalid request), -32601 (method not found), -32602 (invalid params), -32603 (internal error)
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 · 142 lines · 38 tokens per session scan A 494eb5ab78d3
mcp-developer is an agent published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 15d ago), licensed MIT. It adds 38 tokens to every session and 1,189 once invoked, about $0.0002 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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