Graphicle vs MemMachine

Graphicle 67

Read with the API checklist for a server the owner runs, as for Cognee and Graphiti. Over HTTP each person or agent gets its own key with a role, optional expiry and optional project list, stored as a hash, revocable, and sent in a header with the docs saying never in the URL. The stdio server runs with the owner key, which can read every project, and its graph tools take repo to reach other projects (24 of 30). The MCP server has no delete or command tool, agent writes are drafts that a person approves, and --tools and per-key project revocation narrow access. No approval step is needed because nothing destructive is exposed (18 of 20). Recall returns documents, connector content and captured sessions, which can carry injected text. Server instructions say memory is evidence, not tool permission, drafts need verbatim quotes, and capture redacts credentials and drops <private> spans. No general prompt-injection guidance found (9 of 15). Workspace usage counters, workflow_status and hash-chained deletion receipts, while the team audit trail belongs to the commercial edition (6 of 15). SECURITY.md with private reporting through GitHub advisories, a security.txt at karlex.ai valid to 7 April 2027 (re-read on 1 November), a cargo-deny advisory check in CI that failed on 15 October, and ### Security sections in the 0.1.6 and 0.1.7 changelog entries. No bug bounty or certification, and the changelog names no advisory for the 0.1.7 fixes (10 of 20). 24+18+9+6+10 = 67.

MemMachine 41

Framework reading for software the owner runs. The server has no authentication and no security scheme in its OpenAPI document (15 of 30). No read-only mode or confirmation for deletes (5 of 20). No guidance on recalled memories as untrusted text (4 of 15). No audit log on the self-hosted server; the hosted console shows usage (5 of 15). SECURITY.md with GitHub private reporting and a two-business-day acknowledgement, with security-audit and SBOM workflows; no security.txt or certification (12 of 20). Total 41.

Graphicle 85

25 tools with memory proposals on, about 24,600 characters of definitions in the v0.1.10 fixture (15). --tools essentials serves five tools (recall_project, read_project_source, query_graph, get_node, get_neighbors, about 7,400 characters) and is what graphicle setup gives Claude Code; --tools graph or --tools memory serves one half, and leaving out --allow-learning leaves only read tools plus graph_link (10 added back, up from 7 on 15 October, for the essentials set). recall_project takes max_tokens or max_chars, include prefixes and skip_shown, query_graph takes token_budget and depth, and list_projects pages with offset and limit (20). Over-limit projects are refused with a message naming the limit and its setting, 409 marks a stale revision and 429 carries Retry-After, and since 0.1.7 the Python SDK keeps retry_after on its error. MCP error shapes are not documented (12 of 20). 21 tools carry readOnlyHint true and 4 false, all with idempotentHint true and destructiveHint false, there are no destructive tools, and propose_memory requires an idempotency_key that replays the same proposal (20). Only question is required on recall and graph queries. Python and TypeScript SDKs exist, at 0.1.10, but install only from source (8 of 15). 25+20+12+20+8 = 85.

MemMachine 65

Searches take limit and filter options for episodic and semantic results (20 of 25). Memories can be listed and filtered by scope (15 of 20). Validation errors are typed; other failures are less clear, as the 429-to-500 issue shows (10 of 20). No idempotency keys or safe-retry guidance found (5 of 20). Python and TypeScript clients and a five-line quick start, once the import is fixed (15). Total 65.

Graphicle 60

No payment protocol (0). Read with the self-hosted rule. Free under Apache-2.0 with nothing to buy (20). No card or account (20). An agent can install it and run graphicle setup --yes with no signup, as the README suggests (20). The commercial team edition is still in private preview with no prices on karlex.ai on 1 November, so there is no paid option to score. 0+20+20+20 = 60.

MemMachine 40

Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI with no account (20). Total 40.

Graphicle 71

Apache-2.0 with NOTICE files that credit Graphify and every adapted project (30). The README privacy section and the FAQ list every case in which the program uses the network, say there is no telemetry or account, and keep data in one SQLite store with deletion receipts. A grep of the source for outbound hosts found only model providers, connectors and GitHub, which agrees. The karlex.ai privacy policy of 14 March 2025 covers the website, not the software (20 of 30). SECURITY.md lists supported versions. No deprecation policy (3 of 20). No telemetry to opt out of, and the network cases are disclosed, with freshness off and --code-only to limit them (18 of 20). 30+20+3+18 = 71.

MemMachine 57

Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55.

Graphicle 63

Read as local software. Installs from an official Homebrew tap, an install script that checks each archive's SHA-256, or release archives, with macOS and Linux (glibc) on arm64 and x86_64 stated, and since 0.1.5 a Windows preview build that isn't code-signed. No language package registry (20). A public CI workflow formats, lints and tests each of the three crates on macOS and Linux. On 15 October every test job passed on both pushes to main and the cargo-deny job for licences, advisories and sources failed; 0.1.7 (25 October) replaced a yanked crate that cargo-deny warned about, but GitHub's Actions pages weren't readable on 1 November, so the runs are per the 15 October check (18). Outside reports and fixes have been handled in releases (issue #8 on kubernetes speed, pull requests #9 and #10 in 0.1.6 and 0.1.7), but the open issue list couldn't be read on 1 November, so the record is still too thin to judge (15). A dated changelog with eleven releases, each with an "After upgrading" section that names the steps a release needs (re-sync, memories that go stale), but large additions and stored-data changes ship in 0.1.x patch bumps (10). Version 0.1.10, not declared stable (0). 20+18+15+10+0 = 63.

MemMachine 51

Local-software lines, as a server the owner runs. memmachine-server and memmachine-client on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51.