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Agent Replay

mdfifty50-boop/agent-replay-mcp
STDIOregistry active
Summary

Records every action an AI agent takes so you can replay sessions step by step and catch regressions. Provides tools to start and stop recording, log individual actions with inputs, outputs, reasoning and timing, then replay the full sequence. The real utility is in compare_sessions, which diffs two runs and shows you exactly where behavior diverged, and find_divergence_point, which pinpoints the first step that deviated from expected output. Export sessions as JSON for tooling or markdown for human review. Useful when debugging non-deterministic agent behavior, comparing model versions, or proving that a workflow changed between runs. Works over stdio and stores sessions in memory keyed by session ID.

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agent-replay-mcp

MCP server for agent session recording and replay — debug non-deterministic agent behavior with session comparison and divergence detection.

Record every action an agent takes, replay sessions step by step, diff two runs to find behavioral regressions, and pinpoint exactly where an agent diverged from expected output.

Install

npx agent-replay-mcp

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "agent-replay": {
      "command": "npx",
      "args": ["agent-replay-mcp"]
    }
  }
}

From source

git clone https://github.com/mdfifty50-boop/agent-replay-mcp.git
cd agent-replay-mcp
npm install
node src/index.js

Tools

record_session

Start recording all actions for an agent session.

ParamTypeDefaultDescription
agent_idstringrequiredUnique agent identifier
metadataobject{}Optional metadata (task, model, environment)

Returns a session_id for use with other tools.

stop_recording

Stop recording and return a session summary.

ParamTypeDescription
session_idstringSession ID from record_session

Returns: action count, total duration, action type breakdown.

log_action

Log a single action during a recording session.

ParamTypeDefaultDescription
session_idstringrequiredActive session ID
action_typestringrequiredType (tool_call, llm_response, decision, error)
inputanyrequiredInput to the action
outputanyrequiredOutput from the action
reasoningstring""Agent reasoning for this step
duration_msnumber0Action duration in milliseconds

replay_session

Replay a recorded session step by step with full action detail.

ParamTypeDescription
session_idstringSession ID to replay

Returns: complete action sequence with timing, reasoning, inputs, and outputs.

compare_sessions

Behavioral diff between two sessions. Aligns actions by step index and highlights differences.

ParamTypeDescription
session_id_1stringFirst session
session_id_2stringSecond session

Returns: similarity ratio, identical/divergent step counts, first divergence step, and per-step diffs.

find_divergence_point

Find where an agent first deviated from expected output.

ParamTypeDescription
session_idstringSession to analyze
expected_outputanyExpected final output, or array of per-step expected outputs

If expected_output is an array, compares step by step. If a single value, finds the last matching output and flags the next step as the divergence point.

export_session

Export a session for sharing and offline analysis.

ParamTypeDefaultDescription
session_idstringrequiredSession to export
formatstring"json""json" or "markdown"

Markdown format produces a readable transcript with step headers, reasoning, and code blocks.

Resources

URIDescription
agent-replay://sessionsAll recorded sessions with status and action counts

Usage Pattern

1. record_session — start recording at agent launch
2. For each agent action:
   - log_action — capture input, output, reasoning, timing
3. stop_recording — finalize the session
4. Debug:
   - replay_session — review what happened step by step
   - compare_sessions — diff today's run vs yesterday's
   - find_divergence_point — pinpoint where it went wrong
5. Share:
   - export_session — JSON for tooling, markdown for humans

Tests

npm test

License

MIT

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Categories
AI & LLM Tools
Registryactive
Packageagent-replay-mcp
TransportSTDIO
UpdatedApr 24, 2026
View on GitHub

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