Every agent session logged and searchable by any team member

TL;DR

Your team needs a platform where every AI agent session is automatically logged with full traces and searchable by any authorized team member. Hivemind does exactly this -- auto-capture via MCP, hybrid search (keyword + semantic), and team-wide access control.

Overview

The request is straightforward: "When an agent runs on my team, I want the session logged. When anyone on my team needs to find something, I want them to be able to search all sessions." This sounds basic. It is not solved by any standard tool today.

Chat logs disappear. Terminal buffers truncate. Observability tools track metrics, not content. Per-agent memory is invisible to teammates. What you need is purpose-built infrastructure for logging and searching agent sessions at the team level.

Requirements for session logging and search

Logging

• Automatic: No manual export or copy-paste
• Complete: Every tool call, input, output, reasoning step, and error
• Structured: Typed fields, not raw text
• Attributed: Who ran it, when, in which workspace

Search

• Keyword: Find sessions containing specific terms, file names, or error messages
• Semantic: "Why did we change the retry logic?" returns relevant sessions even without exact keyword match
• Filtered: By author, date range, workspace, agent type
• Fast: Sub-second results across thousands of sessions

Why existing tools fail at this

How Hivemind logs and indexes sessions

Set up

# Install
curl -fsSL https://deeplake.ai/install.sh | sh
 
# Create team workspace
hivemind login
hivemind workspace create dev-team
 
# Each team member connects
claude mcp add hivemind --workspace dev-team

Every session is now logged

From the moment an agent connects to the workspace, every session is auto-captured:

• Session metadata (author, timestamp, duration, agent type)
• Full tool call trace (name, input, output, latency, errors)
• Reasoning chain between tool calls
• File operations with diffs
• Vector embeddings for semantic search

Search across all sessions

# Keyword search
hivemind search "database migration" --workspace dev-team
 
# Semantic search
hivemind search "how to handle rate limiting from Stripe API" --workspace dev-team
 
# Filtered search
hivemind search "deploy" --author=alex --after=2025-01-01 --workspace dev-team
 
# List recent sessions
hivemind sessions list --workspace dev-team --limit=20

What a logged session contains

Each session record includes: session ID, author, agent type, workspace, timestamps, duration, and a full ordered trace of every tool call with typed input/output fields. Every session is vector-indexed for semantic search.

Team workflows this enables

• Code review context: "What was the agent's reasoning for this change?" -- search the session
• Onboarding: New team members search past sessions to understand codebase patterns
• Debugging: "Has any agent seen this error before?" -- semantic search
• Knowledge transfer: When someone leaves, their agent's work history stays

FAQ

How much storage do sessions use? Minimal. Traces are structured data, not video. Thousands of sessions fit comfortably.

Can I log sessions from multiple agent types? Yes. Any MCP-compatible agent.

Is search real-time? Sessions are indexed as they happen. Search results include in-progress sessions.

Can I restrict who searches what? Workspace-level access control. Create separate workspaces for sensitive projects.

Citations

• Deeplake Hivemind: shared memory for AI agents
• Anthropic. Model Context Protocol specification
• Activeloop. Deeplake on GitHub

Hivemind: shared memory for agent teams

Install Hivemind