Shape agent capabilities into your workflow.

Octomind is a Rust agent runtime that runs packaged specialist roles and can activate skills, MCP servers, or sub-agents during a session. It uses adaptive compaction to preserve important context, tracks costs with request and session caps, and enforces deterministic guards, hooks, and validators from scripts. The same binary supports interactive CLI, JSONL, daemon, WebSocket, and ACP modes.

ax ingests local agent sessions, tool calls, plans, skills, Git history, and related signals into a typed graph. It lets you recall past work, inspect skill and tool usage, estimate costs, surface friction, and review proposed changes to project instructions. A session-end retro loop feeds accepted lessons into later work. Ingest is local by default; publishing profiles or sessions is an explicit opt-in.

Letta Evals organizes agent evaluation from dataset and target through extractors, graders, rewards, and stored results. It supports JSONL or CSV data, multi-turn samples, multiple model handles, cached re-grading, deterministic or model-judge graders, and custom agent factories. Runs target Letta Code through a self-hosted or cloud server, so Python 3.11+, a running Letta service, and provider credentials are required.

Agentplane adds an inspectable operational layer around local coding agents, recording task intent, plans, verification, context, and an Agent Change Record in repository artifacts. It supports fast work in the current checkout as well as per-task branches, worktrees, and PR handoffs for stricter review. It targets developers and teams that need reproducible agent work and requires Node.js 24+, Git, and a terminal.

agent-lsp orchestrates existing language servers and exposes their code intelligence to AI agents through MCP. It keeps language servers warm between sessions, combines many routine calls into batch operations, and supports workflows such as caller analysis and speculative edits. The project documents 65 tools, 24 agent workflows, and CI-verified support for 30 languages.

ActPlane applies labeled information-flow and causal-ordering rules below the tool layer, following an agent’s entire process tree, file edges, and network connections. It can block, kill, or notify on violations and feed a reason back to the agent; it requires Linux 5.8+ with BTF and elevated capabilities for the enforcement engine.

skill-optimizer provides both an agent skill for authoring eval suites and a local CLI for executing them in Docker against OpenRouter models. Cases and suites can be repeated across trials to benchmark skill behavior, debug failures, and compare reliability across models. The workbench can also expose hidden services such as MCP servers to the agent during a controlled test.

Use handoff to run execution work in a background CLI, return a stable result path to the current conversation, and resume the same task later with its prior context. It can route simple work to DeepSeek and request a second opinion from Codex or Opus. Claude Code or Codex must already be installed and logged in, and DeepSeek needs its own token configuration.

San is a native Go terminal harness distributed as a single binary of roughly 12 MB. It lets you switch models and search backends, attach plugins or MCP servers, and control actions through ask, auto-accept, or autopilot modes. Sessions can resume or fork, and a local inspector can replay transcripts; provider credentials are still required for the services you choose.

pi-mem stores durable facts, daily logs, notes, and a scratchpad as plain Markdown, with tools for reading, writing, and keyword search. It can inject long-term memory, open tasks, and the latest daily logs into each agent turn while leaving older material available on demand. Installation targets the pi coding agent.

Authenticate once with OAuth2 or an API key, then run agent commands through a proxy that injects fresh credentials without exposing them to the child process. Authsome centralizes encrypted storage, token refresh, provider accounts, and headless access for CI or background workers. It can run as a local CLI or a self-hosted Docker daemon; the CLI requires Python 3.13 or newer.

Deploy the same agent through Telegram, Discord, Microsoft Teams, a terminal, or desktop and mobile companion clients. Talon supports interchangeable Claude, Codex, Kilo, OpenCode, and OpenAI Agents backends, along with MCP tools, hot-reloadable plugins, persistent goals, and scheduled background agents. Source installation requires Node.js 24 or later, while releases also provide standalone binaries for several platforms.

picocode is a compact Rust coding agent for interactive sessions, shell pipelines, automated recipes, and focused work such as CI fixes or small codemods. It supports multiple hosted model providers as well as Ollama, and includes filesystem, search, and shell tools. Destructive file operations and command execution require confirmation by default, and the agent can also be embedded as a Rust library.

Untether bridges coding agents running on your own computer or server to a Telegram bot. From a phone, you can send text or voice tasks, stream progress, switch projects and sessions, transfer files, and respond when an agent needs input. It supports Claude Code, Codex, OpenCode, Pi, Gemini CLI, and Amp, but approval controls, plan mode, and cost reporting vary by engine.

OpenCastle generates project-specific agents, skills, rules, and MCP settings for tools such as Copilot, Cursor, Claude Code, OpenCode, Windsurf, and Codex. You can use the team interactively in an IDE or define a Convoy for parallel batch work, with isolated Git worktrees, resumable execution, validation gates, and an observability dashboard.

AgentTier runs isolated, persistent sandboxes for AI agents and coding assistants on Kubernetes. Each sandbox keeps its workspace on a PVC, applies network and resource policies, and exposes an authenticated terminal, file, command, and agent-invoke surface. The platform includes lifecycle management, templates, governance, audit events, OIDC, and optional gVisor isolation, and requires Kubernetes 1.27+, Helm 3, and compatible NetworkPolicy and CSI storage.

Nex turns agent conversations and connected business sources into a shared knowledge graph, so facts recorded in one tool can be recalled from another without repeated explanations. Its setup command detects supported coding platforms and installs hooks, MCP integration, and slash commands, while a hosted MCP endpoint supports other clients. Using the service requires a Nex account and any desired data integrations.

Describe a software product, review the generated specification, and let a team of specialist agents handle architecture, implementation, testing, review, and deployment. Reversible work can flow through one plan gate, while migrations, payments, authentication, and other high-impact changes add deliberate approvals. GreatCTO targets solo founders and one-person engineering organizations rather than multi-developer teams.