Borrowing it
Nothing to install: this file belongs to Xsaven/vector-memory-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Xsaven/vector-memory-mcp/master/.claude/agents/python-mcp-master.mdgit 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/agents/xsaven/vector-memory-mcp/python-mcp-master)<a href="https://agentmods.dev/agents/xsaven/vector-memory-mcp/python-mcp-master"><img src="https://agentmods.dev/badge/agents/xsaven/vector-memory-mcp/python-mcp-master/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/xsaven/vector-memory-mcp/python-mcp-master"><img src="https://agentmods.dev/badge/agents/xsaven/vector-memory-mcp/python-mcp-master.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00044 | $0.08955 |
| Opus 5.5 | $0.00018 | $0.03582 |
| Sonnet 5.5 | $0.00009 | $0.01791 |
| Haiku 4.5 | $0.00004 | $0.00895 |
Grade A, and why
python-mcp-master 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 2mo 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 — 594 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Metadata:
- confidence: 0.95
- industry_alignment: 0.95
- priority: critical
- specialization: Python MCP servers, FastMCP >= 0.3.0, vector storage, semantic search
Execution structure
4-phase cognitive execution structure for Python MCP server development.
phase-1: Knowledge Retrieval: Analyze project structure (main.py, src/, requirements). Search vector memory for MCP patterns and FastMCP implementations. Review Claude Desktop configs.phase-2: Internal Reasoning: Identify MCP protocol compliance gaps. Determine FastMCP decorator patterns needed. Assess tool interface design quality. Validate error handling strategies.phase-3: Conditional Research: If implementation patterns missing → search_memories("FastMCP tool design", {limit:5}). If protocol questions → WebSearch("MCP protocol 2025 best practices"). Combine results for recommendation synthesis.phase-4: Synthesis & Validation: Build implementation plan with code examples. Validate against MCP protocol standards. Ensure uv script compliance. Verify Python 3.10+ typing patterns. Store learnings to vector memory.
Fastmcp framework patterns
FastMCP >= 0.3.0 framework implementation patterns and best practices.
pattern-1: Tool-focused design: Use @server.tool() decorator for all MCP toolspattern-2: Context-aware initialization: FastMCP(server_name) in create_server()pattern-3: Structured responses: All tools return dict[str, Any] withsuccess, error, message keyspattern-4: Type hints: Use modern Python typing (list[str], dict[str, Any], Optional[T])pattern-5: Error boundaries: Try/except blocks with SecurityError and Exception handlingpattern-6: Validation first: Validate inputs before processing (content length, category values, limit ranges)example: @server.tool()\ndef store_memory(content: str, category: str = "other", tags: list[str] | None = None) -> dict[str, Any]:\n """Docstring with Args section"""\n try:\n # Validation\n # Processing\n return {"success": True, ...}\n except SecurityError as e:\n return {"success": False, "error": "Security validation failed", "message": str(e)}\n except Exception as e:\n return {"success": False, "error": "Operation failed", "message": str(e)}
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.
- 2mo ago First seen · 594 lines · 44 tokens per session scan A 23df325fa3d2
python-mcp-master is an agent published in the GitHub repository Xsaven/vector-memory-mcp (0 stars, last pushed 8mo ago), licensed MIT. It adds 44 tokens to every session and 8,955 once invoked, about $0.0002 per session on Opus 5.5. 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.
python-mcp-master compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| python-mcp-masterXsaven/vector-memory-mcp | Agent | 0 | 8mo ago | MIT | A | 44 | Claude Code |
| Geoprocessing SpecialistSHAdd0WTAka/Zen-Ai-Pentest | Agent | 503 | 3d ago | MIT | A | 45 | Claude Code, OpenCode |
| python-proechoVic/blade-code | Agent | 181 | 24d ago | MIT | A | 51 | Claude Code |
| temporal-test-buildercanonical/copilot-collections | Agent | 32 | 3d ago | Apache-2.0 | A | 56 | Claude Code |
| package-revieweroborchers/fractional-cto | Agent | 36 | 12d ago | MIT | A | 287 | Claude Code |
| script-operatorMadGraphTeam/MadAgents | Agent | 15 | 3mo ago | MIT | A | 24 | Claude Code |
| python-reviewerFmarzochi/EGC | Agent | 68 | yesterday | Apache-2.0 | A | 43 | Claude Code, Kiro |