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Bristlecone-Logic/bristlecone-logic

by Various

Deterministic guardrails and M2M security rails for autonomous AI agents: pre-socket SSRF defense, zero-overhead JSON repair, and sandboxed AST math verification.

MCP

Bristlecone-Logic/bristlecone-logic

Added 16 Sept 2026

#agentic-workflow #ai-agents #fastmcp #guardrails #jso #json-repair #mcp #mcp-server

Overview

Deterministic guardrails and M2M security rails for autonomous AI agents. It provides pre-socket SSRF defense, zero-overhead JSON repair, and sandboxed AST math verification. Written in Python.

Best for

Best for
Developers building Python-based autonomous agents that need deterministic safety rails

Use cases

  • Block SSRF attempts before socket connections are made
  • Repair malformed JSON output from AI agents without performance overhead
  • Verify mathematical computations using sandboxed AST analysis

How to use

Tools exposed

  • audit_dns
  • chunk_text
  • eval_expression
  • extract_web
  • repair_json
  • validate_schema

Tested with

Claude Desktop

Example client config

{\n  "mcpServers": {\n    "bristlecone-guard": {\n      "url": "https://bristleconelogic.com/mcp"\n    }\n  }\n}

Notes

Deterministic guardrails and M2M security rails for autonomous AI agents. It provides pre-socket SSRF defense, zero-overhead JSON repair, and sandboxed AST math verification. Written in Python.

0 stars on GitHub. Last updated 2026-09-13.

Use cases

  • Block SSRF attempts before socket connections are made
  • Repair malformed JSON output from AI agents without performance overhead
  • Verify mathematical computations using sandboxed AST analysis

Pros

  • Deterministic behavior, not probabilistic
  • Covers security and data integrity in one library
  • Zero-overhead JSON repair is a practical performance advantage

Cons

  • Zero GitHub stars indicates no proven community traction
  • Vendor is listed as Various, so no dedicated support or maintenance guarantee
  • Limited to Python environments

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Deterministic behavior, not probabilistic
  • Covers security and data integrity in one library
  • Zero-overhead JSON repair is a practical performance advantage

Cons

  • Zero GitHub stars indicates no proven community traction
  • Vendor is listed as Various, so no dedicated support or maintenance guarantee
  • Limited to Python environments
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