Tigerless agent-memory
Tigerless agent-memory: Open-source, self-hosted agent memory with Markdown storage and local retrieval. Ranked #26 of 34 in AI Agent Memory Tools by our editors (5.6/10); pricing: Free plan; best for solo developers preferring local Markdown memory.
At a glance
- Editor score5.6 / 10
- PricingFree plan
- Best forSolo developers preferring local Markdown memory
- Free planYes
- Paid fromNone
- Semantic memoryYes
- Facts checked13 Oct 2026
Where it wins
- Markdown remains the canonical, portable memory store
- BM25 retrieval plus optional vector fusion runs locally
- Lifecycle hooks and proposal workflows manage memory over time
Where it doesn't
- Self-hosted deployment requires installation from source with Python and uv
- Support is provided through documentation
- Local-only deployment may not suit teams seeking a hosted service
Our verdict on Tigerless agent-memory
Tigerless agent-memory is an open-source runtime for giving AI agents persistent, long-term memory on a self-hosted machine. Markdown files remain the source of truth, while a rebuildable SQLite index supports ranked local retrieval. The design covers session-start injection, boundary-time writes, consolidation, and sleep-time management, with validity intervals, superseding, merging, and deletion for lifecycle control. It is aimed at solo developers and small teams that want inspectable files and local operation rather than a hosted memory service.
There is no paid tier: the project is open source with a free plan. Its retrieval stack uses BM25 through FTS5 and can add vector retrieval with reciprocal-rank fusion. Command-line and stdio MCP interfaces connect the same store to Claude Code, Codex CLI, Muse Code, Hermes, and other shell-capable agents. This shared-store approach fits workflows that move between several coding assistants while keeping memory in one local repository. No API key is required, which keeps the runtime focused on local infrastructure.
Setup is oriented toward technical users: installation is from source with Python and uv, followed by self-hosted operation. Documentation is the stated support channel, so teams looking for managed onboarding or service-level assistance may prefer a hosted alternative. The strongest case for Tigerless is a developer who wants direct control over Markdown memory, configurable retention, and explicit proposal-based management. It is less suitable for organizations that need vendor-managed deployment, centralized administration, or support beyond project documentation.
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Tigerless agent-memory pricing
Tigerless agent-memory fact sheet
| Free plan | Yes |
|---|---|
| Paid from | None |
| Semantic memory | Yes |
| Episodic memory | Yes |
| User/profile memory | Not verified |
| Graph-based memory | Yes |
| Deployment options | Self_hosted |
| SDK languages | Not verified |
| Retention policy | Configurable |
| Deployment | Self-hosted |
| Support | Docs |
| Built for | Solo, Small business (editorial estimate) |
| Integrations | 4 integrations: Claude Code, Codex CLI, Muse Code, Hermes |
| Pricing | Free plan |
| Website | github.com |
| Facts checked | 13 Oct 2026 |
Tigerless agent-memory integrations
Tigerless agent-memory lists 4 integrations on its own site.
- Claude Code
- Codex CLI
- Muse Code
- Hermes
Alternatives to Tigerless agent-memory
- Cloudflare Agent MemoryA cloud API for scoped, searchable memory across AI agent profiles and conversations.9.2
- Mem0A flexible memory layer with semantic, graph, and self-hosted deployment options.8.8
- MCP Memory ServiceA broad open-source memory layer for teams that can manage deployment and configuration.7.9
See all Tigerless agent-memory alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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