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/jspv/google_search_mcp/copilot-instructionsgit clone --depth 1 https://github.com/jspv/google_search_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/instructions/jspv/google_search_mcp/copilot-instructions)<a href="https://agentmods.dev/instructions/jspv/google_search_mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/jspv/google_search_mcp/copilot-instructions.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 | $0.00906 | $0.00906 |
| Opus 5 | $0.00453 | $0.00453 |
| Sonnet 5 | $0.00181 | $0.00181 |
| Haiku 4.5 | $0.00091 | $0.00091 |
Grade A, and why
google_search_mcp copilot-instructions.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 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copilot instructions for google_search_mcp
Purpose: Give AI coding agents the minimum, high‑signal context to work productively in this repo.
What this repo is
- An MCP server exposing one tool: Google Programmable Search (CSE).
- Same logic runs in 3 surfaces: stdio (default), HTTP over SSE, and Streamable HTTP; plus adapters for AWS Lambda and containers.
Architecture (files you’ll touch)
server.py— FastMCP server with a single tool@mcp.tool() async def search(...). Uses one sharedhttpx.AsyncClient_http(HTTP/2). Config via Dynaconf (GOOGLE_*). Import‑time check requiresGOOGLE_API_KEYandGOOGLE_CX.- Behavior:
numclamped 1..10,safemust beoff|active, optionalALLOW_DOMAINSfilter, lean responses viafieldswhenlean_fields=True. - Return shape (do not change casually):
{provider, query, searchInfo, nextPage, latency_ms, results[], raw, trace}. Secrets are never echoed (no API key;cxomitted).
- Behavior:
server_http.py— ASGI SSE app from the samemcpinstance; exposes standard MCP endpoints/sseand/messages(not a custom REST API). CORS viaCORS_ORIGINS("*" default). On shutdown, awaits_http.aclose().server_http_stream.py— Streamable HTTP transport variant; same CORS and shutdown behavior.lambda_handler.py— Bridges Bedrock AgentCore Gateway to the stdio server by spawningpython -m serverand explicitly passing env.Dockerfile.mcp— Multi‑mode container;MCP_MODE=stdio|http|http-stream(port 8000 by default).- Schema tooling:
scripts/dump_tool_schema.pyanddeploy_aws_agentcore_auth0/gen_tool_schema.sh.
Workflows
- Install deps:
uv sync(+ extras as needed:--extra http,--extra lambda,--extra container). - Run servers:
uv run python -m server|HOST=0.0.0.0 PORT=8000 uv run python -m server_http|uv run python -m server_http_stream. - Tests:
uv run pytest -q(VS Code Task: “Run tests”). Tests patch env and mock HTTP; no real Google calls.
Conventions and patterns
- Always reuse the global
_httpclient; do not create per‑request clients. Ensure it’s closed on app shutdown (tests assertaclose()awaited). - No custom REST endpoints; only MCP transports. For middleware, attach to the Starlette app in
get_app(). - Config precedence: environment variables override
.env(Dynaconf).DYNACONF_DOTENV_PATHis honored. - Logging is opt‑in via
GOOGLE_LOG_*: logs go to stderr by default; optionally toGOOGLE_LOG_FILE. Query text is logged only ifGOOGLE_LOG_QUERY_TEXT=true(hash otherwise).
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 · 46 lines · 906 tokens per session scan A a5c4b901abd8
google_search_mcp copilot-instructions.md is an instructions file published in the GitHub repository jspv/google_search_mcp (0 stars, last pushed 10mo ago), licensed MIT. It adds 906 tokens to every session, about $0.0045 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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