vector-memory-mcp: Agent for Claude Code

.claude/agents/python-mcp-master.md

python-mcp-master is an agent for Claude Code from Xsaven/vector-memory-mcp. It costs 44 tokens per session (8,955 once invoked), scanned A, original, MIT.

A specialist for building Python servers that let AI tools call functions through the Model Context Protocol, a standard for connecting AI applications to external tools.

In plain words
What is it for?
Use it to design or review FastMCP servers, define their tools, check protocol compliance, configure Claude Desktop, and set up Python projects with uv.
Why use it?
It helps avoid protocol mistakes and unclear tool designs when creating these servers. It also addresses common issues with Python's asynchronous code and desktop integration.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions subagents.

This is Xsaven/vector-memory-mcp's own configuration. It tells Claude Code how to work on vector-memory-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything vector-memory-mcp configures →

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /Users/user/project/run-arm64.sh.

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/Xsaven/vector-memory-mcp/master/.claude/agents/python-mcp-master.md
Clone the repo
git clone --depth 1 https://github.com/Xsaven/vector-memory-mcp

Made for: Claude Code.

Wrote 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.

agentmods badge for python-mcp-master

README.md
[![agentmods](https://agentmods.dev/badge/agents/xsaven/vector-memory-mcp/python-mcp-master/github.svg)](https://agentmods.dev/agents/xsaven/vector-memory-mcp/python-mcp-master)
Your own site
<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.

agentmods 80×15 button for python-mcp-master

Your own site · 80×15
<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>
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 8,955 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 2mo ago against content hash 23df325fa3d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

.claude/agents/python-mcp-master.md · 594 lines

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 tools
  • pattern-2: Context-aware initialization: FastMCP(server_name) in create_server()
  • pattern-3: Structured responses: All tools return dict[str, Any] with success, error, message keys
  • pattern-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 handling
  • pattern-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)}

Read the full file on GitHub · 594 lines

Changes

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.

  1. 2mo ago First seen · 594 lines · 44 tokens per session scan A 23df325fa3d2

Subscribe to this mod's changes

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.

Related

python-mcp-master compared with agents from other repositories

python-mcp-master next to 6 agents from other repositories
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