Daily AI Implementation Scout Council

#1

newtest firstBoth runtimes28 / 35

Supermemory tool

An open-source memory and context engine with an MCP server and a Claude Code plugin that gives agents fast, self-hostable memory across sessions.

What it does for you: Lets Axion remember MCL context (Marc's brand rules, past content decisions, client facts) across sessions instead of re-explaining each time. It ships a CLAUDE.md and a skills folder, so it drops into your setup almost directly.

In practice: You ask Axion something next week and it already knows the context you gave it today.

For: Both runtimes. Ships an MCP server plus a Claude Code plugin, and is callable from any runtime.

Security3

Quality4

Auditability3

Useful to you5

Useful to community5

Buildable now4

Hermes4

Verdict: test first. Directly droppable via the Claude plugin, but its benchmark wins are self-reported, so trial on your data.

Build #1 Supermemory: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/supermemoryai/supermemory. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 27.2k stars, active main branch; ships CLAUDE.md + skills/; claims LongMemEval/LoCoMo/ConvoMem leads (self-reported).

#2

newtest firstBoth runtimes28 / 35

Graphiti framework

An open-source engine that builds real-time, time-aware knowledge graphs for agents (facts with validity windows, automatic contradiction handling).

What it does for you: Gives Axion/Hermes a memory that tracks how facts about your clients, projects, and business change over time, with fast hybrid retrieval. Stronger than flat text memory for relationship and timeline questions.

In practice: You ask 'what changed with this client since March' and it answers from the graph.

For: Both runtimes. A standalone temporal-memory engine with an MCP server either runtime can call.

Security3

Quality5

Auditability3

Useful to you5

Useful to community5

Buildable now3

Hermes4

Verdict: test first. Powerful and well-backed, but needs a graph DB (Neo4j/FalkorDB), which is extra local infra.

Build #2 Graphiti: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/getzep/graphiti. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 27.7k stars, 2.8k forks, pushed 2026-06-20, Apache-2.0; arXiv 2501.13956.

#3

newbuild nowClaude (Axion)29 / 35

awesome-claude-code-subagents skill

A curated library of 100+ single-file Claude Code subagent definitions by category, plus a catalog skill to search and fetch them.

What it does for you: Lets you drop battle-tested agent files straight into your .claude/agents layout, and its on-demand catalog skill is a clean template for an Axion/Hermes agent loader.

In practice: You browse the catalog, pick an agent, and it is in your project in seconds.

For: Claude (Axion). A library of Claude Code subagent definition files for the .claude/agents layout.

Security3

Quality4

Auditability4

Useful to you5

Useful to community5

Buildable now5

Hermes3

Verdict: build now. Directly compatible with your file-based agents; just review each file's tool grants.

Build #3 awesome-claude-code-subagents: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/VoltAgent/awesome-claude-code-subagents. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~22.2k stars, last commit 2026-06-16, MIT.

#4

newtest firstBoth runtimes30 / 35

promptfoo tool

An open-source CLI/library to evaluate and red-team prompts, agents, and RAG pipelines via declarative configs, with adversarial scanning and CI integration.

What it does for you: Lets you put Axion/Hermes prompts and MCL-facing agents under regression and safety tests in CI, so a prompt tweak cannot silently break or expose the system.

In practice: You change a prompt, the test suite runs, and it flags the one case that regressed.

For: Both runtimes. A model-agnostic eval/red-team CLI either runtime can run in CI.

Security4

Quality5

Auditability4

Useful to you4

Useful to community5

Buildable now4

Hermes4

Verdict: test first. High-value eval/safety layer; the config has a learning curve and attack suites cost tokens.

Build #4 promptfoo: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/promptfoo/promptfoo. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 13k+ stars, MIT, used by OpenAI/Anthropic; OpenAI acquired it Mar 2026, still open source.

#5

newtest firstBoth runtimes30 / 35

Pydantic AI framework

A type-safe Python agent framework from the Pydantic team with validated structured outputs, tool calling, and native Logfire tracing.

What it does for you: Gives Axion/Hermes guaranteed-schema outputs (no brittle JSON parsing) plus first-class observability, ideal where MCL workflows need reliable structured data out of the LLM.

In practice: You ask for a structured result and get a validated object every time, not a maybe-JSON string.

For: Both runtimes. A Python agent framework either runtime can call for typed outputs.

Security4

Quality5

Auditability4

Useful to you4

Useful to community5

Buildable now4

Hermes4

Verdict: test first. Clean fit for reliable outputs; Python-only and durable-execution features add infra if adopted.

Build #5 Pydantic AI: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/pydantic/pydantic-ai. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · MIT, very active 2026 releases, from the Pydantic/Logfire team.

#6

newbuild nowBoth runtimes31 / 35

Agentic Design Patterns Catalog pattern

A consolidated 12-pattern taxonomy merging Ng's 4 patterns, Anthropic's 5 workflow patterns, and 2025-2026 reliability/memory patterns, with maturity ratings and framework mappings.

What it does for you: Gives you a shared vocabulary and decision framework (Reflection, Tool Use, ReAct, Planning, Evaluator-Optimizer, Human-in-the-Loop, memory patterns) for designing more reliable Axion/Hermes agents and skills.

In practice: You design a new agent and pick a named, proven pattern instead of inventing structure.

For: Both runtimes. A vendor-neutral pattern reference that applies to any runtime.

Security5

Quality4

Auditability4

Useful to you4

Useful to community5

Buildable now5

Hermes4

Verdict: build now. Pure leverage, no install; apply the patterns to your agent designs.

Build #6 Agentic Design Patterns Catalog: use the ai-implementation-build-intake skill to build this safely. Source: https://www.augmentcode.com/guides/agentic-design-patterns. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · Repeatedly cited 2026 consolidation; corroborated by LangChain's 2026 State of Agent Engineering report.

#7

newtest firstBoth runtimes26 / 35

Archon framework

An open-source harness builder that wraps coding agents in deterministic YAML workflows (plan, loop-until-tests-pass, human approval, PR) with isolated git worktrees.

What it does for you: Turns your ad-hoc agent builds into reproducible pipelines, exactly what your build-intake gate wants, running fresh-context loops and deterministic gates so Hermes ships predictably.

In practice: You define a build once as a workflow and it runs the same way every time.

For: Both runtimes. A harness builder that wraps coding agents (Claude Code and others via MCP).

Security4

Quality4

Auditability3

Useful to you5

Useful to community4

Buildable now3

Hermes3

Verdict: test first. Strong fit for your build gate, but it is mid v1-to-v2 rewrite so docs/APIs shift.

Build #7 Archon: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/coleam00/Archon. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~22.5k stars, 3.4k forks; v2 harness rewrite, works with Claude Code via MCP.

#8

newtest firstBoth runtimes26 / 35

memU framework

A framework that ingests multimodal sources and auto-organizes typed memories (profile/event/knowledge/skill/tool) into navigable folders with embeddings.

What it does for you: Gives MasteryCollective a self-organizing memory of client conversations, docs, and call recordings that any agent can retrieve as scoped context, without manual tagging. Its file-folder model matches your 2nd-Brain layout.

In practice: You drop a call transcript in and it files itself into the right memory folders.

For: Both runtimes. A file-system-as-memory framework callable from either runtime.

Security3

Quality4

Auditability4

Useful to you5

Useful to community4

Buildable now3

Hermes3

Verdict: test first. Fits your file-based brain, but needs Python 3.13+ and an LLM key, and defaults to OpenAI.

Build #8 memU: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/NevaMind-AI/memU. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~13.9k stars, 1.0k forks; pip memu-py, SQLite/Postgres+pgvector backends.

#9

newtest firstBoth runtimes27 / 35

AgentMemory tool

An MCP memory server that gives AI coding agents persistent, benchmarked long-term memory across sessions.

What it does for you: Plugs into Axion/Hermes so your agents remember prior decisions, file context, and project state instead of starting cold each session, cutting repeated explanation.

In practice: Your coding agent recalls last week's decisions on the same project.

For: Both runtimes. An MCP memory server either runtime can attach.

Security3

Quality4

Auditability3

Useful to you4

Useful to community5

Buildable now4

Hermes4

Verdict: test first. Easy MCP attach, but it is a crowded space, so validate its claims on your workload.

Build #9 AgentMemory: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/rohitg00/agentmemory. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~23.5k stars, last push 2026-06-15, Apache-2.0.

#10

newtest firstBoth runtimes26 / 35

Beads tool

A distributed, git-native graph issue tracker for AI coding agents (Steve Yegge), with dependency tracking and context-window memory compaction.

What it does for you: Lets Hermes/Claude Code persist long-horizon tasks and their dependencies across sessions and branches, so multi-step builds survive context resets, the exact problem that bit this project.

In practice: A long build remembers its open tasks and dependencies after any restart.

For: Both runtimes. A git-native task tracker with an MCP server either runtime can use.

Security3

Quality4

Auditability3

Useful to you4

Useful to community5

Buildable now3

Hermes4

Verdict: test first. Solves long-task persistence, but it is young, just renamed orgs, and depends on Dolt.

Build #10 Beads: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/steveyegge/beads. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~24.7k stars; npm @beads/bd + PyPI beads-mcp, MCP server included.

#11

newtest firstStandalone tool25 / 35

activepieces framework

Open-source, self-hostable workflow automation with AI agents and ~400 MCP servers/integrations, plus a visual builder (an n8n/Zapier alternative).

What it does for you: Becomes the connective tissue for MCL ops (lead intake, onboarding, follow-up, content distribution), wiring CRM, calendar, payments, and email into visual flows a solo operator can maintain.

In practice: A new lead triggers a flow that books, emails, and logs them automatically.

For: Standalone tool. A self-hosted automation platform you operate, not a runtime component.

Security3

Quality5

Auditability3

Useful to you4

Useful to community5

Buildable now3

Hermes2

Verdict: test first. Strong ops backbone, but self-hosting is real infra and some pieces are commercially licensed.

Build #11 activepieces: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/activepieces/activepieces. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~22.9k stars, pushed 2026-06-20; MIT core with some commercial packages.

#12

newtest firstStandalone tool26 / 35

listmonk tool

A high-performance, self-hosted newsletter and mailing-list manager as a single Go binary with a dashboard and HTTP API.

What it does for you: Could run MCL's whole email/newsletter engine at near-zero marginal cost, and its API is exactly what your AI-scout newsletter cron could publish into for real subscriber delivery.

In practice: Your daily scout newsletter emails itself to your list via one API call.

For: Standalone tool. A self-hosted email engine with an API you publish into, not a runtime component.

Security3

Quality5

Auditability3

Useful to you4

Useful to community5

Buildable now4

Hermes2

Verdict: test first. Mature and cheap, but you must wire an SMTP relay and own deliverability.

Build #12 listmonk: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/knadh/listmonk. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~21.7k stars, pushed 2026-06-20, AGPL-3.0.

#13

newwatchBoth runtimes26 / 35

Agno + AgentOS framework

A high-performance Python agent framework plus AgentOS, a self-hostable FastAPI runtime with sessions, memory, traces, RBAC, scheduling, and 100+ integrations.

What it does for you: A batteries-included backend you could self-host to give Axion/Hermes persistent memory, scheduling, and a real API in your own DB, useful for productizing MasteryCollective agents.

In practice: You deploy one service and your agents get memory, scheduling, and an API.

For: Both runtimes. A self-hostable Python agent runtime either system can build on.

Security3

Quality5

Auditability3

Useful to you4

Useful to community5

Buildable now3

Hermes3

Verdict: watch. Capable and fast, but adopting AgentOS means buying into its whole stack.

Build #13 Agno + AgentOS: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/agno-agi/agno. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · v2.6.18 (Jun 18 2026), 201 releases; claims ~529x faster agent instantiation vs LangGraph.

#14

newtest firstStandalone tool22 / 35

F5-TTS model

A zero-shot voice-cloning TTS: upload a short clip and it speaks any new text in that voice.

What it does for you: For MasteryCollective, clone a coach's voice once and mass-produce narration for reels, course modules, and audiograms without re-recording.

In practice: You type a script and it comes back in Marc's voice, ready to post.

For: Standalone tool. A voice model you run via a Space or self-host, not a runtime component.

Security2

Quality4

Auditability2

Useful to you5

Useful to community4

Buildable now3

Hermes2

Verdict: test first. High MCL content payoff, but voice cloning carries consent/likeness rules.

Build #14 F5-TTS: use the ai-implementation-build-intake skill to build this safely. Source: https://huggingface.co/spaces/mrfakename/E2-F5-TTS. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~2.88k likes (Space), last modified 2026-05-20, runnable in-browser or self-host.

#15

newwatchBoth runtimes25 / 35

microsoft/agent-framework framework

Microsoft's open-source SDK and runtime for orchestrating multi-agent workflows with one API across Python and .NET (unifying Semantic Kernel + AutoGen), with OpenTelemetry tracing.

What it does for you: An orchestration backbone if Axion/Hermes outgrows single-agent loops, with workflow/handoff primitives and tracing to coordinate multi-step coaching automations.

In practice: You wire several agents into one traced workflow with handoffs.

For: Both runtimes. A multi-agent orchestration SDK (Python + .NET) usable by either system.

Security4

Quality5

Auditability3

Useful to you3

Useful to community5

Buildable now2

Hermes3

Verdict: watch. Heavyweight and Azure-leaning; overkill while you stay within the Claude Agent SDK.

Build #15 microsoft/agent-framework: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/microsoft/agent-framework. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~11.5k stars, pushed 2026-06-20, v1.0 April 2026, MIT.

#16

newwatchStandalone tool23 / 35

Qwen3-Coder-Next model

A compact MoE coding model (~3B active params) that holds up reliably inside agent loops like Cline, Aider, and OpenHands.

What it does for you: Lets you run a capable local coding model on a 16GB machine for offline or zero-API-cost build tasks, reducing dependence on paid frontier APIs for routine work.

In practice: Routine coding runs happen locally for free; you save the frontier model for hard problems.

For: Standalone tool. A local model you serve and point tools at, not a runtime component.

Security3

Quality4

Auditability2

Useful to you4

Useful to community4

Buildable now3

Hermes3

Verdict: watch. Good cost-saving tier, but local quality trails frontier Claude for hard reasoning.

Build #16 Qwen3-Coder-Next: use the ai-implementation-build-intake skill to build this safely. Source: https://huggingface.co/Qwen/Qwen3-Coder-Next. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~1.47k likes, 1.09M downloads, last update 2026-02-03, apache-2.0.

#17

newwatchStandalone tool24 / 35

OpenCode tool

A provider-agnostic open-source terminal AI coding agent (TUI + LSP) that runs any model, not just one vendor's.

What it does for you: A fallback or complement to Claude Code for build work that can drive local or alternate models, useful when Claude limits bite or for cheaper bulk coding runs.

In practice: When you hit a limit, you switch to another model in the same terminal flow.

For: Standalone tool. A standalone terminal coding agent you run, provider-agnostic.

Security3

Quality4

Auditability3

Useful to you3

Useful to community5

Buildable now3

Hermes3

Verdict: watch. Solid alternative, but org rename signals governance flux and the space is crowded.

Build #17 OpenCode: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/anomalyco/opencode. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · 1274 HN points; 825 releases, v1.17.8 Jun 17 2026; npm opencode-ai (org renamed sst to anomalyco).

#18

newwatchBoth runtimes23 / 35

MemOS framework

A self-evolving memory operating system for LLM agents with graph-structured memory, hybrid retrieval, and cross-task skill reuse.

What it does for you: Gives Axion/Hermes an inspectable, editable memory graph (not a black-box vector store) that reuses learned skills across tasks and reports token savings, lowering run cost.

In practice: You can open and edit what your agent remembers, like a map.

For: Both runtimes. A self-hostable memory layer either runtime can call.

Security3

Quality4

Auditability3

Useful to you4

Useful to community4

Buildable now2

Hermes3

Verdict: watch. Promising but heavier architecture than a simple memory layer; revisit after lighter options.

Build #18 MemOS: use the ai-implementation-build-intake skill to build this safely. Source: https://github.com/MemTensor/MemOS. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · ~9.9k stars, last push 2026-06-18, arXiv 2505.22101, Apache-2.0 (confirm).

#19

newwatchStandalone tool19 / 35

Databox MCP product

An MCP connector that lets you query live business analytics (marketing, sales, revenue KPIs) in plain language inside Claude, ChatGPT, or n8n.

What it does for you: You could ask 'how did MCL's paid campaigns do last week' directly in Claude and get answers from live data, skipping dashboard-hopping for ops reporting.

In practice: You ask Axion a KPI question and it answers from your real numbers.

For: Standalone tool. A SaaS analytics connector you subscribe to, queried via MCP.

Security2

Quality4

Auditability1

Useful to you4

Useful to community3

Buildable now3

Hermes2

Verdict: watch. Useful for ops reporting, but depends on first wiring MCL data into Databox and another subscription.

Build #19 Databox MCP: use the ai-implementation-build-intake skill to build this safely. Source: https://www.producthunt.com/products/databox. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · Launched June 1 2026, #3 Product of the Day, on the durable Databox platform.

#20

newwatchStandalone tool18 / 35

Mina Meeting Assistant product

An AI meeting teammate that joins live calls, answers in real time, and generates summaries, proposals, follow-ups, and CRM updates during the call.

What it does for you: For MCL sales/coaching calls it can draft follow-ups, capture action items, and push CRM updates live, cutting post-call admin so the team stays on the conversation.

In practice: After a call, the summary and follow-ups are already written.

For: Standalone tool. A SaaS meeting assistant you use directly, not a runtime component.

Security2

Quality3

Auditability1

Useful to you4

Useful to community3

Buildable now3

Hermes2

Verdict: watch. Useful for call admin, but real-time interjection is hype-prone and needs guardrails on live coaching calls.

Build #20 Mina Meeting Assistant: use the ai-implementation-build-intake skill to build this safely. Source: https://www.producthunt.com/products/mina-meeting-assistant. Save canonical skill/agent under AXION\Skills and AXION\Agents. Copy

Source · #1 on PH June 1 2026 (~497 votes); integrates HubSpot, Salesforce, Slack.