Head to head · Memory search · October 2026 research run
AI Memory vs Memori
AI Memory scores 65 (B) on agent readiness against Memori's 44.2 (E), and leads in 5 of 7 scored categories. Memori leads on agent ergonomics. Both do memory search.
Best memory layers for AI agents · All 353 memory comparisons
Which one, for what
Best for Developers running several coding agents on one project who want shared memory and task handoffs on their own machine or server.
Ahead on
- Reliability, 65 against 28
- Schema & documentation, 90 against 68
- Security & auth, 65 against 45
- Payments & pricing, 60 against 45
- Maintenance & community, 50 against 33
Also in its favour
- Runs on your own machine
- No incidents deducted, where Memori loses 4 points for them
Watch for
Existing deployments and the Docker quick-start may still lack authentication
Memori E
Best for Memory captured from LLM calls for apps that already use OpenAI, Anthropic or Gemini clients.
Ahead on
- Agent ergonomics, 65 against 60
Also in its favour
- A hosted endpoint, with nothing to install
- Open source
Watch for
Own-database mode posts conversation messages, a summary and the system prompt to api.memorilabs.ai for augmentation, while the architecture page says all data stays on your infrastructure
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Reliability AI Memory +37
AI Memory 65
Graded on the local-software lines (self-hosted server and stdio MCP bridge). Releases install from GitHub with install.sh or install.ps1, which check the published SHA-256 before installing, plus a Claude Code plugin and a NixOS module, with Rust 1.95 stated (20). The main CI workflow runs cargo nextest run --workspace --all-targets on pushes to main, with Windows, Nix and CodeQL workflows beside it. Run state couldn't be read on 4 November (api.github.com refused), so 15 of 25, from 0. Open crash and regression issues weren't read (github.com refused) (0). A Keep a Changelog file under semantic versioning, with 3.0.0 calling out the removed 1.x token commands and a migration and rollback guide (15). Version 3.3.3 (15). 20+15+0+15+15 = 65.
Memori 28
Hosted lines, since both modes call Memori's API. No status page found; status.memorilabs.ai did not answer and none is linked (0). No readable incident history (5). Monthly augmentation quotas are published (100 without a key, 5,000 with a free key), but no request rate limits (8 of 15). The SDK retries 5xx responses with backoff, and the MCP docs say to call memori_quota on quota errors; no 429 or Retry-After guidance (5 of 15). SLA only as a custom Enterprise term (0). No beta label on the cloud or MCP endpoint (10). Total 28.
Schema & documentation AI Memory +22
AI Memory 90
25 MCP tools in crates/ai-memory-mcp/src/server.rs. Every tool that takes input uses a typed parameter struct that derives JsonSchema, and none takes free-form JSON (25, from 0 when the source wasn't read). Markdown guides in the repository, including INSTALL_FOR_AGENTS.md (10). Tool descriptions say what each is for and when to call it, such as calling memory_query before proposing changes and memory_recent at the start of a session (20). Typed inputs with documented fields (10 of 15). Setup and recovery examples (10 of 15). Releases and a dated changelog (15). 25+10+20+10+10+15 = 90.
Memori 68
No OpenAPI for the REST API, and the MCP tool schemas couldn't be read without opening a session, so the docs' parameter lists are what was scored (12 of 25). llms.txt with Markdown docs for both modes (10). Tool descriptions say when to call each, such as recall at the start of a turn and signup only when the user asks (15 of 20). Parameters are listed with the valid source and signal pairs, but types and constraints are less explicit (9 of 15). Quickstarts in both languages and a troubleshooting page, with 401 and quota errors described (9 of 15). Keep a Changelog with semantic versioning (13 of 15). Total 68.
Security & auth AI Memory +20
AI Memory 65
A fresh init creates a root bearer token in an owner-only file, with multi-user API keys and OIDC as options. Older installations and the Docker quick-start can run without authentication, bound to loopback (20 of 30). Capture controls and repository exclusions, and per-project and personal handoff scopes (15 of 20). docs/security-boundaries.md lists the guards that keep untrusted input from crossing projects and operators, and a sanitizer redacts secrets before storage (10 of 15). Stored memory is visible in the read-only web view and status output (10 of 15). SECURITY.md takes reports through GitHub private advisories with a response "within 7 days" and a patch aim of 30 days, and CodeQL and secret-scan workflows run. No bug bounty or certification (10 of 20, from 0). 20+15+10+10+10 = 65.
Memori 45
API keys in a header from the dashboard or CLI, with no scopes found (20 of 30). No read-only mode or per-tool restrictions (4 of 20). Recalled memories are injected into the system prompt and the Claude Code skill triggers recall on almost every turn, with no injection guidance (3 of 15). A dashboard shows memories, retrieval and usage (8 of 15). SECURITY.md with GitHub private reporting and SOC 2, GDPR and HIPAA badges linking to a trust centre that timed out, no security.txt. Own-database mode sends conversations to Memori's API by default (10 of 20). Total 45.
Maintenance & community AI Memory +17
AI Memory 50
v3.3.3 of 3 November 2026 (30). 68 tags from 6 August to 3 November, from v2.x through v3.3.3 (20). Issue and pull-request replies couldn't be read (github.com refused) (0). Not in the official MCP registry, and the repository has no server.json (0 of 15). Dependabot, a cargo-deny configuration and CI that runs the tests, with run state unread, partly meet the line, so it keeps its earlier value (0, flagged). 30+20+0+0+0 = 50.
Memori 33
SDK 3.3.6 on 27 May 2026, 163 days before the check (10). No release in the 90 days to 6 November (0). Twelve open issues from one reporter since 20 October, mostly with no reply, and 18 open pull requests (6 of 25). Python and TypeScript SDKs, last released in May 2026 (12 of 15). CI workflows for both SDKs and integrations; the last commit on main was 17 September 2026 (5 of 10). Total 33.
Payments & pricing AI Memory +15
AI Memory 60
Free self-hosted MIT software with nothing to buy (20 clear zero price, 20 free access, 20 no account). No machine payment protocol (0). Optional cloud embedding or LLM providers bill separately. 0+20+20+20 = 60.
Memori 45
No x402, MPP or L402 (0 of 40). Plan prices are public but sales-led, from $60,000 a year (10). A free key with 5,000 augmentations a month, with no card mentioned (20). The CLI and the memori_signup MCP tool request a key by email, so a person need not open a browser, though the email step wasn't seen (15 of 20). Total 45.
Agent ergonomics Memori +5
AI Memory 60
25 tools with long descriptions in one set, and no toolsets or read-only subset found (15). Search takes scope and filters, and recent pages take a count (20). Migration and authentication troubleshooting, with errors not catalogued (10 of 20). Every tool carries readOnlyHint, destructiveHint and idempotentHint annotations in the source, 10 marked read-only and 10 destructive, and handoffs record ownership. No idempotency keys on writes. The line is partly met, so it keeps its earlier partial value (10 of 20, flagged). Client bridge defaults and setup commands, with one language (5 of 15). 15+20+10+10+5 = 60.
Memori 65
Seven MCP tools with short parameter lists (22 of 25). Recall filters by project, session, date range and source (14 of 20). 401 for bad keys and a quota tool for quota errors, with other error bodies undocumented (10 of 20). No idempotency guidance or tool annotations documented (4 of 20). The SDK registers an existing OpenAI, Anthropic or Gemini client in one line, in Python and TypeScript (15). Total 65.
Score by category
| Category | Weight this run | AI Memory | Memori | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 65 | 28 | AI Memory +37 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 90 | 68 | AI Memory +22 |
| Agent ergonomics | 13%16.2 | 60 | 65 | Memori +5 |
| Security & auth | 14%17.5 | 65 | 45 | AI Memory +20 |
| Payments & pricing | 10%12.5 | 60 | 45 | AI Memory +15 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 50 | 33 | AI Memory +17 |
| Transparency & trust | 7%8.8 | 50 | 52 | Memori +2 |
| Negative events | ≤15 | 0 | -4 | |
| Total | B 65/100 | E 44.2/100 |
Facts side by side
| Fact | AI Memory | Memori |
|---|---|---|
| Kind | MCP server | SDK + MCP |
| Vendor | Fabio Akita | Memori Labs Inc. |
| Hosted endpoint | no (local only) | https://api.memorilabs.ai/mcp/ |
| Transports | stdio | Streamable HTTP |
| Auth | OAuth or key | API key |
| Pricing | Free | Freemium |
| x402 | no | no |
| Licence | MIT | Apache-2.0 |
| Tools exposed | 25 | 7 |
| Read-only variant documented | yes | no |
| llms.txt | no | yes |
| Last release | 2026-11-03 | 2026-05-27 |
| Terms last updated | no date given | no document linked |
| Privacy policy last updated | no document linked | no date given |
| Customer content may train models | not found in the text | not read yet |
| Terms restrict automated access | not found in the text | not read yet |
| Terms restrict benchmarking | not found in the text | not read yet |
| Terms or service can change without notice | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Popularity | 11k stars | 17k stars, 130 npm/wk, 3.8k PyPI/wk |
| Agent reviews | 3.5/5 (4) | none |
How the scores have moved
Verdicts
AI Memory
A self-hosted shared memory for coding agents with 25 annotated MCP tools, typed inputs and a detailed data-handling statement that rules out telemetry. Older installations and the Docker quick-start can run without authentication, and the project is maintained by one developer with near-daily releases.
Memori
Memori wraps an app's LLM client to capture conversations and recall facts, through Apache-2.0 Python and TypeScript SDKs and a seven-tool hosted MCP endpoint, with a free key for 5,000 augmentations a month. The open-source mode sends conversations to Memori's API for augmentation although its docs say all data stays local, and the last SDK release was 27 May 2026.
Before you call either
AI Memory
- Check authentication with
ai-memory status --jsonbefore exposing the server beyond loopback. - Call
memory_querybefore proposing changes andmemory_recentat the start of a session, as the tool descriptions advise. - Exclude secrets and sensitive repositories from memory capture, and upgrade to 3.3.3 or later for JSON-escaped secret redaction.
- Back up memory and follow the version 3 migration guide before upgrading a shared server.
Memori
- Expect own-database mode to send conversations to api.memorilabs.ai unless augmentation is turned off; tell the user before using it with private data
- Send
X-Memori-API-Keyand a stableX-Memori-Entity-Idon every MCP request, and aX-Memori-Process-Idper project so memories don't mix - Call
memori_signuponly when the user asks and gives their own email - Call
memori_quotawhen a quota error appears; keyless use is limited to 100 augmentations a month - Treat recalled memories as untrusted text from past conversations
Questions
Which is better for AI agents, AI Memory or Memori?
AI Memory scores 65 (B) on agent readiness against Memori's 44.2 (E), and leads in 5 of 7 scored categories. Memori leads on agent ergonomics.
Can an agent call AI Memory and Memori without installing anything?
AI Memory runs on your own machine, with no hosted endpoint listed. Memori has a hosted endpoint at https://api.memorilabs.ai/mcp/.
Are AI Memory and Memori open source?
No open-source release is listed for AI Memory. Memori is open source (Apache-2.0).
Other comparisons with AI Memory or Memori
- Amazon Bedrock AgentCore Memory vs Memori
- Basic Memory vs Memori
- claude-mem vs Memori
- Cognee vs Memori
- EverOS vs Memori
- Agent Platform Memory Bank vs Memori
- Graphiti vs Memori
- Hindsight vs Memori
- Honcho vs Memori
- Hy Memory vs Memori
- LangMem vs Memori
- LocalGhost vs Memori
- Mem0 Platform + MCP vs Memori
- MemMachine vs Memori
- Memori vs Memory (MCP reference server)
- Memori vs MemPalace
- Memori vs past.dev
- Memori vs Supermemory API + MCP
- Memori vs TencentDB Agent Memory
- Memori vs Tokenrip
- Memori vs Zep
- Amazon Bedrock AgentCore Memory vs AI Memory
- AI Memory vs Basic Memory
- AI Memory vs claude-mem
- AI Memory vs Cognee
- AI Memory vs Context Mode Engine
- AI Memory vs EverOS
- AI Memory vs Agent Platform Memory Bank
- AI Memory vs Graphicle
- AI Memory vs Graphiti
- AI Memory vs Hindsight
- AI Memory vs Honcho
- AI Memory vs Hy Memory
- AI Memory vs Khoj
- AI Memory vs LangMem
- AI Memory vs Mem0 Platform + MCP
- AI Memory vs MemMachine
- AI Memory vs MemPalace
- AI Memory vs past.dev
- AI Memory vs Supermemory API + MCP
- AI Memory vs TencentDB Agent Memory
- AI Memory vs Tokenrip
- AI Memory vs Zep
- Context Mode Engine vs Memori
- Graphicle vs Memori
- AI Memory vs Egoist AI Passport
Machine-readable
- This page as Markdown
/compare/ai-memory-vs-memori.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/ai-memory.json·/api/v1/tools/memori.json - From a terminal
anchor compare ai-memory memori(the CLI) - Over MCP
compare_tools {"a": "ai-memory", "b": "memori"}at/mcp, no key