An agent composition framework that builds stacks and compiles specialized subagents for Claude Code

MCP server: structured-output enforcer for any LLM. Wraps @mukundakatta/agentcast.

MCP server: validate tool-call args before execution. Wraps @mukundakatta/agentvet.

MCP server: token-aware message truncation. Wraps @mukundakatta/agentfit.

MCP server: declarative network-egress firewall for agent tools. Wraps @mukundakatta/agentguard.

Validate LLM-generated tool args before execution. Wrap your tools with a schema; throws ToolArgError with an LLM-friendly retry hint. Zero deps.

Snapshot tests for AI agents — record tool-call traces, diff against baselines, fail CI on regressions. Zero deps.

Python port of @mukundakatta/agentvet: validate LLM-generated tool args before execution

MCP server for @mukundakatta/agentbudget — token + dollar budget caps for AI agents over stdio. Drop into Claude Desktop, Cursor, Cline, Windsurf, Zed.

Network egress firewall for AI agents — declarative allowlist of domains an agent's tools can fetch, throws on violation. Zero deps.

The agent reliability stack in one install: fit, guard, snap, vet, cast.

The Agent Reliability Stack: fit, guard, snap, vet, cast. One landing page for all 11 npm + 6 PyPI packages.

Token + dollar budget caps for AI agents — raises BudgetExceededError when an LLM call would push past the ceiling. Zero deps, drop into any provider SDK. Python port of @mukundakatta/agentbudget.

MCP server: snapshot tests for tool-call traces. Wraps @mukundakatta/agentsnap.

Python port of @mukundakatta/agentfit: fit your messages into the LLM context window

The agent reliability stack in one install: fit + guard + snap + vet + cast (Python ports).

GitHub Action for AI agent tool-call snapshot tests. Diffs current traces against baselines, posts PR comments on drift. Wraps @mukundakatta/agentsnap.

Structured output for any LLM call — validate, retry with feedback, return typed data or throw. Zero deps. Sibling to agentsnap + agentguard.

Cost and latency tracking for AI agent runs. Wraps your LLM call, returns a per-step + per-run breakdown.

Token + dollar budget caps for AI agents — throws when an LLM call would push past the ceiling. Zero deps, drop into any provider SDK.