BloodHound MCP, One Year Later: What I Learned About MCPs, Models, and Context
specterops.io | blog | #ai-security
Summary
The first version of BloodHound MCP proved that an LLM could converse with BloodHound. The current version drove home the lesson that MCP design is context design. The most useful changes were smaller but more flexible tools, better error recovery, domain-specific resources, and a prompt that guides the model instead of trying to teach everything up front.
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- Collected
--- id: 9405 title: "BloodHound MCP, One Year Later: What I Learned About MCPs, Models, and Context" source_domain: specterops.io source_url: "https://specterops.io/blog/2026/06/18/bloodhound-mcp-one-year-later-what-i-learned-about-mcps-models-and-context/" published_at: "2026-06-18T16:30:00Z" tags: ["ai-security"] phying_url: "https://phying.com/item/9405" lang: en --- # BloodHound MCP, One Year Later: What I Learned About MCPs, Models, and Context ## Summary The first version of BloodHound MCP proved that an LLM could converse with BloodHound. The current version drove home the lesson that MCP design is context design. The most useful changes were smaller but more flexible tools, better error recovery, domain-specific resources, and a prompt that guides the model instead of trying to teach everything up front. ## Intelligence Metadata - **Sources:** specterops.io - **Published:** 2026-06-18T16:30:00Z - **Original:** https://specterops.io/blog/2026/06/18/bloodhound-mcp-one-year-later-what-i-learned-about-mcps-models-and-context/ - **Phying News:** https://phying.com/item/9405