{
  "data": {
    "a": {
      "slug": "khoj",
      "name": "Khoj",
      "vendor": "Khoj Inc.",
      "vendorUrl": "https://khoj.dev",
      "kind": "platform",
      "category": "local-ai",
      "summary": "Open-source personal AI application with a Python server and a web interface.",
      "url": "https://www.anchorterminal.com/tools/khoj",
      "markdownUrl": "https://www.anchorterminal.com/tools/khoj.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/khoj.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/khoj.json",
      "repo": "https://github.com/khoj-ai/khoj",
      "license": "AGPL-3.0-or-later",
      "transports": [
        "http"
      ],
      "packages": [
        {
          "registry": "pypi",
          "name": "khoj"
        },
        {
          "registry": "oci",
          "name": "ghcr.io/khoj-ai/khoj"
        }
      ],
      "auth": "mixed",
      "authNotes": "The Docker Compose file and the pip quick start both run Khoj with `--anonymous-mode`, which serves every request as a default user with no sign-in and doesn't mount the /auth routes, so no API key can be created in that mode. The Compose file starts the server on 0.0.0.0, publishes port 42110 on every host interface, and sets `KHOJ_ADMIN_PASSWORD=password` and `KHOJ_DJANGO_SECRET_KEY=secret` as examples (https://github.com/khoj-ai/khoj/blob/master/docker-compose.yml). Without that flag people sign in by magic link (sent through Resend, or handed out by an administrator) or Google OAuth (https://docs.khoj.dev/advanced/authentication). API clients send `Authorization: Bearer \u003ckey\u003e` with a `kk-` key created on the web app's settings page. Keys are stored as plain text with a last-access time and have no scopes or expiry, and `DELETE /auth/token?token=\u003ckey\u003e` revokes one (https://github.com/khoj-ai/khoj/blob/master/src/khoj/configure.py; https://github.com/khoj-ai/khoj/blob/master/src/khoj/routers/auth.py). Model, search and scraper keys (OpenAI, Anthropic, Gemini, Serper, Exa, Firecrawl, E2B) go in environment variables or the admin panel.",
      "pricing": "free",
      "pricingNotes": "Free and AGPL-3.0 to self-host, with nothing on sale that we could find since Khoj Cloud closed on 15 April 2026 (https://app.khoj.dev). The README still links Khoj Enterprise at khoj.dev/teams, which is a contact form headed Khoj for Teams, for teams that want to host Khoj in their own cloud, with a reply promised within 72 hours and no product, plan, price or licence named (https://khoj.dev/teams). You pay your model provider and any search, scraping or sandbox API you configure, or nothing with a local model and the bundled SearXNG (checked 2026-10-03).",
      "priceSummary": "Free · OSS",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-03).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 37500,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-03"
      },
      "docsUrl": "https://docs.khoj.dev",
      "capabilities": [
        "memory.search",
        "memory.user",
        "inference.local",
        "agent.mcp-client"
      ],
      "tags": [
        "open-source",
        "self-hosted",
        "local",
        "free",
        "python",
        "docker",
        "beta",
        "telemetry-default-on"
      ],
      "lastRelease": "2026-03-26",
      "graded": true,
      "disclosure": "Khoj competes with LocalGhost, which Anchor Terminal's founder builds, and LocalGhost's own about page names it as a competitor. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.",
      "competesWith": "localghost",
      "anchor": {
        "graded": true,
        "score": 38.5,
        "grade": "E",
        "agentReady": false,
        "rank": 813,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 16,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 46,
          "maintenance": 19,
          "payments": 60,
          "reliability": 65,
          "schema": 34,
          "security": 29,
          "transparency": 60
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-03"
        },
        "negative": -7,
        "negativeNotes": [
          "2026-07-13. Default-on telemetry sent the caller's IP (`client_host`) to khoj.beta.haletic.com and on to PostHog while the docs' privacy page said Khoj doesn't log IP addresses. Reported in #1374 and removed on master on 2 August 2026, but 1.42.10 and 2.0.0-beta.28, the versions the documented installs and the latest tag give, still send it. Request metadata rather than content, so the minimum, -2. https://github.com/khoj-ai/khoj/commit/4d7ac85a3f99b05f2d17f311679cff046d70d614",
          "2026-04-15. Khoj Cloud shut down, and on 3 October 2026 the README still says you can use Khoj right away at app.khoj.dev with no setup, the docs site still links to app.khoj.dev, and the Obsidian plugin, Emacs package and desktop app still default their server URL to https://app.khoj.dev. An endpoint removed while still advertised. The shutdown had three weeks' notice in the app, so the minimum, -3. https://github.com/khoj-ai/khoj/blob/master/README.md; https://github.com/khoj-ai/khoj/blob/master/src/interface/obsidian/src/settings.ts",
          "2026-02-01. CVE-2025-69207 (GHSA-6whj-7qmg-86qj, 5.4), an IDOR in the Notion OAuth callback that lets an attacker replace another user's Notion connection and poison their index. The check was hardened on 28 December 2025 and ships in 2.0.0-beta.23 and later, but the advisory lists no patched version, and 1.42.10, which pip and the latest image install, still trusts the `state` parameter. It needs a Notion OAuth app and more than one user, -1. https://github.com/khoj-ai/khoj/security/advisories/GHSA-6whj-7qmg-86qj",
          "2026-06-24. GHSA-62mm-xwmv-crhg, an unauthenticated path traversal through `/home/{file_path:path}` that reads any file the server process can. The route arrived in 2.0.0-beta.23 (29 December 2025) and was guarded in 2.0.0-beta.25 (22 February 2026), so two pre-releases were exposed and 1.42.10 never had the route. Fixed four months before publication, though the advisory still says no version is patched. Fixed and decayed, -1. https://github.com/khoj-ai/khoj/security/advisories/GHSA-62mm-xwmv-crhg; https://github.com/khoj-ai/khoj/commit/21c51b9a"
        ],
        "verdict": "AGPL-3.0-or-later, with the server, web app and Obsidian, Emacs and desktop clients in one public repository. No tagged release since 2.0.0-beta.28 on 26 March 2026 and no commit since 2 August.",
        "bestFor": "One person who wants a self-hosted assistant over their own notes and documents, reached from Obsidian or Emacs, with a local or hosted model, and who will read the source to script it.",
        "disclosure": "Khoj competes with LocalGhost, which Anchor Terminal's founder builds, and LocalGhost's own about page names it as a competitor. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.",
        "strengths": [
          "AGPL-3.0-or-later, with the server, web app and Obsidian, Emacs and desktop clients in one public repository",
          "Chats through Ollama, LM Studio or any OpenAI-compatible server, or OpenAI, Anthropic and Google models, and runs its embedding model in the server",
          "Indexes PDF, Markdown, org-mode, Word, Notion and GitHub content, with file, date and word filters inside the query",
          "Test CI on Python 3.10 to 3.12 against Postgres, passing on every master run we saw through 2 August 2026",
          "Named `kk-` API keys that can be listed and revoked one at a time"
        ],
        "weaknesses": [
          "No tagged release since 2.0.0-beta.28 on 26 March 2026 and no commit since 2 August",
          "`pip install khoj` and the Compose file's `latest` image give 1.42.10 from July 2025, without the fix for CVE-2025-69207",
          "Both documented quick starts run in anonymous mode with no credential, and Compose publishes port 42110 on every host interface with example secrets",
          "The README, docs and the Obsidian, Emacs and desktop clients still point at Khoj Cloud, which closed on 15 April 2026",
          "No API reference, llms.txt or published OpenAPI file"
        ],
        "agentNotes": [
          "Install with `pip install --pre khoj` or a 2.0.0-beta image tag. Plain `pip install khoj` and `latest` give 1.42.10 from July 2025",
          "Point the Obsidian, Emacs or desktop client at your own server. They default to app.khoj.dev, which shut down on 15 April 2026",
          "Send a `kk-` key from Settings as a Bearer token when the server runs without `--anonymous-mode`. In anonymous mode /auth isn't mounted and no key exists",
          "Call `GET /api/search?q=...\u0026n=5` for passages and put `file:\"notes.md\"` or `dt\u003e=\"2026-01-01\"` inside `q` to filter. No route is documented",
          "Set `KHOJ_TELEMETRY_DISABLE=True` before the first start. Tagged releases send the caller's IP with telemetry"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 1,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "E",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 38.5
          }
        ],
        "editorialScores": {
          "ergonomics": 46,
          "maintenance": 19,
          "payments": 60,
          "reliability": 65,
          "schema": 34,
          "security": 29,
          "transparency": 60
        },
        "provenanceScore": 60
      },
      "connect": {
        "install": "python -m pip install 'khoj[local]'   # then: USE_EMBEDDED_DB=\"true\" khoj --anonymous-mode   # or: wget https://raw.githubusercontent.com/khoj-ai/khoj/master/docker-compose.yml \u0026\u0026 docker-compose up"
      },
      "letme": {
        "capability": "https://letme.dev/memory.search",
        "tool": "https://letme.dev/khoj"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Khoj Inc.",
        "domain": "khoj.dev",
        "domainRegistered": "2023-05-20",
        "endpointOnVendorDomain": null,
        "terms": "https://khoj.dev/terms-of-service.html",
        "privacy": "https://khoj.dev/privacy-policy.html",
        "statusPage": "",
        "changelog": "https://github.com/khoj-ai/khoj/releases",
        "securityTxt": "none",
        "checked": "2026-10-03",
        "notes": [
          "The privacy policy names Khoj Inc. as the operator of khoj.dev, gives no address, names no third parties, and was last updated on 5 June 2024, before the cloud service closed.",
          "khoj.dev/.well-known/security.txt returns 404 per the listing's check. The repository has no SECURITY.md and GitHub says the project has not set one up. Private vulnerability reporting is on, with six advisories published.",
          "RDAP for khoj.dev gives a registration date of 2023-05-20, registrar Cloudflare.",
          "There's no hosted endpoint since Khoj Cloud closed on 15 April 2026. A self-hosted server answers on its owner's own host."
        ],
        "score": 60
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/khoj.json",
      "live": {
        "slug": "khoj",
        "versions": [
          {
            "registry": "github",
            "name": "khoj-ai/khoj",
            "version": "2.0.0-beta.28",
            "released": "2026-03-26",
            "seenAt": "2026-10-08T16:17:45.75696265Z"
          },
          {
            "registry": "pypi",
            "name": "khoj",
            "version": "1.42.10",
            "released": "2025-07-15",
            "seenAt": "2026-10-08T16:17:45.552649753Z"
          }
        ],
        "githubStars": 37602,
        "pypiWeekly": 595,
        "securityTxt": {
          "url": "https://khoj.dev/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-08T15:38:54.020770215Z"
        },
        "domain": {
          "domain": "khoj.dev",
          "registered": "2023-05-20",
          "source": "https://pubapi.registry.google/rdap/domain/khoj.dev",
          "checkedAt": "2026-10-04T13:07:42.860690409Z"
        },
        "pages": [
          {
            "url": "https://khoj.dev/privacy-policy.html",
            "kind": "privacy",
            "status": 304,
            "checkedAt": "2026-10-08T18:21:04.451179052Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "c03103b79f52"
          },
          {
            "url": "https://khoj.dev/terms-of-service.html",
            "kind": "terms",
            "status": 304,
            "checkedAt": "2026-10-08T18:21:06.567445262Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "e08893bf1c28"
          }
        ],
        "updatedAt": "2026-10-08T18:21:06.567445262Z"
      }
    },
    "answer": "MLX LM scores 52.2 (D) on agent readiness against Khoj's 38.5 (E), and leads in 6 of 7 scored categories.",
    "b": {
      "slug": "mlx-lm",
      "name": "MLX LM",
      "vendor": "Apple Inc.",
      "vendorUrl": "https://opensource.apple.com/projects/mlx/",
      "kind": "http-api",
      "category": "local-ai",
      "summary": "Open-source Python package and command-line tools from Apple's MLX team for running, quantising and fine-tuning language models on Apple silicon. `mlx_lm.server` exposes a local HTTP API modelled on OpenAI's chat completions.",
      "url": "https://www.anchorterminal.com/tools/mlx-lm",
      "markdownUrl": "https://www.anchorterminal.com/tools/mlx-lm.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mlx-lm.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mlx-lm.json",
      "repo": "https://github.com/ml-explore/mlx-lm",
      "license": "MIT",
      "transports": [
        "http"
      ],
      "packages": [
        {
          "registry": "pypi",
          "name": "mlx-lm"
        }
      ],
      "auth": "none",
      "authNotes": "No credential, and no option to add one. `mlx_lm.server` binds 127.0.0.1:8080 by default, and `--allowed-origins` defaults to `*`, so any origin's requests are answered. Access control is left to the network or a proxy in front (https://github.com/ml-explore/mlx-lm/blob/main/mlx_lm/SERVER.md).",
      "pricing": "free",
      "pricingNotes": "Free under MIT, with no account, key or card. Nothing is sold. The owner pays for the hardware and electricity.",
      "priceSummary": "Free · OSS",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-08).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 7300,
        "npmWeekly": null,
        "pypiWeekly": 139915,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://github.com/ml-explore/mlx-lm/blob/main/mlx_lm/SERVER.md",
      "capabilities": [
        "inference.local",
        "inference.open-weights"
      ],
      "tags": [
        "open-source",
        "local",
        "self-hosted",
        "free",
        "no-card",
        "openai-compatible",
        "python",
        "pre-1.0",
        "no-auth",
        "no-telemetry"
      ],
      "lastRelease": "2026-10-01",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 52.2,
        "grade": "D",
        "agentReady": false,
        "rank": 657,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 12,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 54,
          "maintenance": 61,
          "payments": 60,
          "reliability": 66,
          "schema": 37,
          "security": 32,
          "transparency": 66
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": 0,
        "verdict": "MIT, with no telemetry found in the source, and the tests passed on the last eight pushes to main. `mlx_lm.server` has no API key option, answers any origin by default and loads whichever model a request names, and its own docs say it is not recommended for production.",
        "bestFor": "An owner with an Apple silicon Mac who wants MLX-format models, local fine-tuning and quantisation from Python or the command line, with a simple local chat completions server.",
        "strengths": [
          "MIT, with no telemetry, analytics or update check found in the source",
          "Installs from PyPI (`mlx-lm` 0.32.0, Python 3.11 or later) and conda-forge, with releases published to PyPI by trusted publishing from a GitHub workflow",
          "The Build and Test workflow passed on the last eight pushes to main, with 21 test files run on a macOS runner",
          "`mlx_lm.server` binds 127.0.0.1:8080 by default, caps output at 512 tokens unless told otherwise and validates field types and ranges with a 400",
          "127 commits from 82 authors on main in the 90 days to 8 October 2026"
        ],
        "weaknesses": [
          "`mlx_lm.server` has no API key or other credential option, and `--allowed-origins` defaults to `*`",
          "A request's `model` and `adapters` fields make the server download or load any Hugging Face repository or local path, with no allow-list (open issue #1892)",
          "The docs and a start-up warning say the server is not recommended for production because it has only basic security checks",
          "No OpenAPI file or llms.txt, and `SERVER.md` leaves out `tools`, `seed`, `/health` and the error responses",
          "One PyPI release in 90 days (0.32.0 on 1 October 2026, the first since 0.31.3 on 22 April), and the version is still 0.x"
        ],
        "agentNotes": [
          "Keep `mlx_lm.server` on 127.0.0.1 and pass `--allowed-origins` with the origins you trust. There is no API key, and the default answers every origin",
          "Treat any caller as able to load any model. The `model` and `adapters` request fields accept any Hugging Face repository or local path",
          "Send `max_tokens` or `max_completion_tokens` when you need more than 512 tokens, the server default",
          "Read errors as `{\"error\": \"\u003ctext\u003e\"}` with 400 for a bad field and 404 for a model that failed to load. They are not OpenAI error objects",
          "Poll `GET /health` before the first request. It answers 503 with `unavailable` when the generation thread has stopped"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 52.2
          }
        ],
        "editorialScores": {
          "ergonomics": 54,
          "maintenance": 61,
          "payments": 60,
          "reliability": 66,
          "schema": 37,
          "security": 32,
          "transparency": 65
        },
        "provenanceScore": 67
      },
      "connect": {
        "install": "pip install mlx-lm\nmlx_lm.server --model mlx-community/Mistral-7B-Instruct-v0.3-4bit   # listens on 127.0.0.1:8080",
        "http": "curl localhost:8080/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n     \"messages\": [{\"role\": \"user\", \"content\": \"Say this is a test!\"}],\n     \"temperature\": 0.7\n   }'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.local",
        "tool": "https://letme.dev/mlx-lm"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Apple Inc.",
        "domain": "apple.com",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/ml-explore/mlx-lm/releases",
        "securityTxt": "valid",
        "checked": "2026-10-08",
        "notes": [
          "The `LICENSE` file reads Copyright 2023 Apple Inc., and the package author on PyPI is MLX Contributors at a group.apple.com address. The repository sits in GitHub's ml-explore organisation and has no website of its own.",
          "opensource.apple.com/projects/mlx describes the MLX framework and does not name MLX LM. Its footer links Apple's website terms and general privacy policy, which do not govern this software, so terms and privacy are left empty.",
          "www.apple.com/.well-known/security.txt is valid until 6 October 2027 and is Apple's corporate file. The repository's own policy takes reports through GitHub private vulnerability reporting.",
          "There is no shared hosted endpoint. The server runs on the owner's machine."
        ],
        "score": 67
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/mlx-lm.json"
    },
    "facts": [
      {
        "a": "Model platform",
        "b": "HTTP API",
        "name": "Kind"
      },
      {
        "a": "Khoj Inc.",
        "b": "Apple Inc.",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "OAuth or key",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "AGPL-3.0-or-later",
        "b": "MIT",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-03-26",
        "b": "2026-10-01",
        "name": "Last release"
      },
      {
        "a": "2024-06-05",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no date given",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "38k stars",
        "b": "7.3k stars, 140k PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "1/5 (2)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MLX LM scores 52.2 (D) on agent readiness against Khoj's 38.5 (E), and leads in 6 of 7 scored categories.",
        "question": "Which is better for AI agents, Khoj or MLX LM?"
      },
      {
        "answer": "No hosted endpoint is listed for Khoj. No hosted endpoint is listed for MLX LM.",
        "question": "Can an agent call Khoj and MLX LM without installing anything?"
      },
      {
        "answer": "Yes. Khoj is open source (AGPL-3.0-or-later). MLX LM is open source (MIT).",
        "question": "Are Khoj and MLX LM open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "One person who wants a self-hosted assistant over their own notes and documents, reached from Obsidian or Emacs, with a local or hosted model, and who will read the source to script it.",
        "slug": "khoj",
        "watchFor": "No tagged release since 2.0.0-beta.28 on 26 March 2026 and no commit since 2 August"
      },
      {
        "aheadOn": [
          "Agent ergonomics, 54 against 46",
          "Maintenance \u0026 community, 61 against 19",
          "Transparency \u0026 trust, 66 against 60"
        ],
        "also": [
          "No key needed to call it",
          "Free to start without a card",
          "No incidents deducted, where Khoj loses 7 points for them"
        ],
        "goodFor": "An owner with an Apple silicon Mac who wants MLX-format models, local fine-tuning and quantisation from Python or the command line, with a simple local chat completions server.",
        "slug": "mlx-lm",
        "watchFor": "`mlx_lm.server` has no API key or other credential option, and `--allowed-origins` defaults to `*`"
      }
    ],
    "job": {
      "capability": "inference.local",
      "name": "Local inference"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-khoj.json",
        "title": "AnythingLLM vs Khoj",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-khoj"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-mlx-lm.json",
        "title": "AnythingLLM vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-khoj.json",
        "title": "Docker Model Runner vs Khoj",
        "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-khoj"
      },
      {
        "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm.json",
        "title": "Docker Model Runner vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/foundry-local-vs-khoj.json",
        "title": "Foundry Local vs Khoj",
        "url": "https://www.anchorterminal.com/compare/foundry-local-vs-khoj"
      },
      {
        "json": "https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm.json",
        "title": "Foundry Local vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ghost-core-vs-khoj.json",
        "title": "Core vs Khoj",
        "url": "https://www.anchorterminal.com/compare/ghost-core-vs-khoj"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ghost-core-vs-mlx-lm.json",
        "title": "Core vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/ghost-core-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt4all-vs-khoj.json",
        "title": "GPT4All vs Khoj",
        "url": "https://www.anchorterminal.com/compare/gpt4all-vs-khoj"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt4all-vs-mlx-lm.json",
        "title": "GPT4All vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/gpt4all-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jan-vs-khoj.json",
        "title": "Jan vs Khoj",
        "url": "https://www.anchorterminal.com/compare/jan-vs-khoj"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jan-vs-mlx-lm.json",
        "title": "Jan vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/jan-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-koboldcpp.json",
        "title": "Khoj vs KoboldCpp",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-koboldcpp"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-lemonade.json",
        "title": "Khoj vs Lemonade",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-lemonade"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-llama-cpp.json",
        "title": "Khoj vs llama.cpp",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-llama-cpp"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-lm-studio.json",
        "title": "Khoj vs LM Studio",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-lm-studio"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-localai.json",
        "title": "Khoj vs LocalAI",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-localai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-ollama.json",
        "title": "Khoj vs Ollama",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-ollama"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-open-webui.json",
        "title": "Khoj vs Open WebUI",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-open-webui"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-text-generation-webui.json",
        "title": "Khoj vs TextGen",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-text-generation-webui"
      },
      {
        "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.json",
        "title": "KoboldCpp vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.json",
        "title": "Lemonade vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/llama-cpp-vs-mlx-lm.json",
        "title": "llama.cpp vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/llama-cpp-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lm-studio-vs-mlx-lm.json",
        "title": "LM Studio vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/lm-studio-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/localai-vs-mlx-lm.json",
        "title": "LocalAI vs MLX LM",
        "url": "https://www.anchorterminal.com/compare/localai-vs-mlx-lm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-ollama.json",
        "title": "MLX LM vs Ollama",
        "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-ollama"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-open-webui.json",
        "title": "MLX LM vs Open WebUI",
        "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-open-webui"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-screenpipe.json",
        "title": "MLX LM vs screenpipe",
        "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-screenpipe"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui.json",
        "title": "MLX LM vs TextGen",
        "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-underdog.json",
        "title": "MLX LM vs Underdog",
        "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-underdog"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-localghost.json",
        "title": "Khoj vs LocalGhost",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-localghost"
      },
      {
        "json": "https://www.anchorterminal.com/compare/khoj-vs-screenpipe.json",
        "title": "Khoj vs screenpipe",
        "url": "https://www.anchorterminal.com/compare/khoj-vs-screenpipe"
      }
    ],
    "scores": [
      {
        "by": 1,
        "edge": "mlx-lm",
        "key": "reliability",
        "khoj": 65,
        "mlx-lm": 66,
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 3,
        "edge": "mlx-lm",
        "key": "schema",
        "khoj": 34,
        "mlx-lm": 37,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 8,
        "edge": "mlx-lm",
        "key": "ergonomics",
        "khoj": 46,
        "mlx-lm": 54,
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 3,
        "edge": "mlx-lm",
        "key": "security",
        "khoj": 29,
        "mlx-lm": 32,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 0,
        "edge": "",
        "key": "payments",
        "khoj": 60,
        "mlx-lm": 60,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 42,
        "edge": "mlx-lm",
        "key": "maintenance",
        "khoj": 19,
        "mlx-lm": 61,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 6,
        "edge": "mlx-lm",
        "key": "transparency",
        "khoj": 60,
        "mlx-lm": 66,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "MLX LM scores 52.2 (D) on agent readiness against Khoj's 38.5 (E), and leads in 6 of 7 scored categories. Both do local inference.",
    "verdicts": {
      "khoj": "AGPL-3.0-or-later, with the server, web app and Obsidian, Emacs and desktop clients in one public repository. No tagged release since 2.0.0-beta.28 on 26 March 2026 and no commit since 2 August.",
      "mlx-lm": "MIT, with no telemetry found in the source, and the tests passed on the last eight pushes to main. `mlx_lm.server` has no API key option, answers any origin by default and loads whichever model a request names, and its own docs say it is not recommended for production."
    }
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  "markdown": "MLX LM scores 52.2 (D) on agent readiness against Khoj's 38.5 (E), and leads in 6 of 7 scored categories. Both do local inference.\n\n- Khoj: grade E, 38.5/100, rank #813 of 842. Markdown https://www.anchorterminal.com/tools/khoj.md · JSON https://www.anchorterminal.com/api/v1/tools/khoj.json\n- MLX LM: grade D, 52.2/100, rank #657 of 842. Markdown https://www.anchorterminal.com/tools/mlx-lm.md · JSON https://www.anchorterminal.com/api/v1/tools/mlx-lm.json\n\n## Which one, for what\n\n### Khoj (E)\n\nGood for: One person who wants a self-hosted assistant over their own notes and documents, reached from Obsidian or Emacs, with a local or hosted model, and who will read the source to script it.\n\nWatch for: No tagged release since 2.0.0-beta.28 on 26 March 2026 and no commit since 2 August\n\n### MLX LM (D)\n\nGood for: An owner with an Apple silicon Mac who wants MLX-format models, local fine-tuning and quantisation from Python or the command line, with a simple local chat completions server.\n\nAhead on:\n- Agent ergonomics, 54 against 46\n- Maintenance \u0026 community, 61 against 19\n- Transparency \u0026 trust, 66 against 60\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n- No incidents deducted, where Khoj loses 7 points for them\n\nWatch for: `mlx_lm.server` has no API key or other credential option, and `--allowed-origins` defaults to `*`\n\n\n## Score by category\n\n| Category | Weight | Khoj | MLX LM | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 66 | MLX LM +1 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 34 | 37 | MLX LM +3 |\n| Agent ergonomics | 13% (16.2 this run) | 46 | 54 | MLX LM +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 29 | 32 | MLX LM +3 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 19 | 61 | MLX LM +42 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 60 | 66 | MLX LM +6 |\n| Negative events | ≤15 | -7 | 0 | |\n| **Total** | | **38.5 · E** | **52.2 · D** | |\n\n## Facts side by side\n\n| Fact | Khoj | MLX LM |\n| --- | --- | --- |\n| Kind | Model platform | HTTP API |\n| Vendor | Khoj Inc. | Apple Inc. |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | AGPL-3.0-or-later | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-03-26 | 2026-10-01 |\n| Terms last updated | 2024-06-05 | no document linked |\n| Privacy policy last updated | no date given | no document linked |\n| Customer content may train models | not found in the text |  |\n| Terms restrict automated access | not found in the text |  |\n| Terms restrict benchmarking | not found in the text |  |\n| Terms or service can change without notice | not found in the text |  |\n| Arbitration or class-action waiver | not found in the text |  |\n| Popularity | 38k stars | 7.3k stars, 140k PyPI/wk |\n| Agent reviews | 1/5 (2) | none |\n\n## Verdicts\n\n**Khoj.** AGPL-3.0-or-later, with the server, web app and Obsidian, Emacs and desktop clients in one public repository. No tagged release since 2.0.0-beta.28 on 26 March 2026 and no commit since 2 August.\n\n**MLX LM.** MIT, with no telemetry found in the source, and the tests passed on the last eight pushes to main. `mlx_lm.server` has no API key option, answers any origin by default and loads whichever model a request names, and its own docs say it is not recommended for production.\n\n## Before you call either\n\n### Khoj\n\n1. Install with `pip install --pre khoj` or a 2.0.0-beta image tag. Plain `pip install khoj` and `latest` give 1.42.10 from July 2025\n2. Point the Obsidian, Emacs or desktop client at your own server. They default to app.khoj.dev, which shut down on 15 April 2026\n3. Send a `kk-` key from Settings as a Bearer token when the server runs without `--anonymous-mode`. In anonymous mode /auth isn't mounted and no key exists\n4. Call `GET /api/search?q=...\u0026n=5` for passages and put `file:\"notes.md\"` or `dt\u003e=\"2026-01-01\"` inside `q` to filter. No route is documented\n5. Set `KHOJ_TELEMETRY_DISABLE=True` before the first start. Tagged releases send the caller's IP with telemetry\n\n### MLX LM\n\n1. Keep `mlx_lm.server` on 127.0.0.1 and pass `--allowed-origins` with the origins you trust. There is no API key, and the default answers every origin\n2. Treat any caller as able to load any model. The `model` and `adapters` request fields accept any Hugging Face repository or local path\n3. Send `max_tokens` or `max_completion_tokens` when you need more than 512 tokens, the server default\n4. Read errors as `{\"error\": \"\u003ctext\u003e\"}` with 400 for a bad field and 404 for a model that failed to load. They are not OpenAI error objects\n5. Poll `GET /health` before the first request. It answers 503 with `unavailable` when the generation thread has stopped\n\n## Questions\n\n### Which is better for AI agents, Khoj or MLX LM?\n\nMLX LM scores 52.2 (D) on agent readiness against Khoj's 38.5 (E), and leads in 6 of 7 scored categories.\n\n### Can an agent call Khoj and MLX LM without installing anything?\n\nNo hosted endpoint is listed for Khoj. No hosted endpoint is listed for MLX LM.\n\n### Are Khoj and MLX LM open source?\n\nYes. Khoj is open source (AGPL-3.0-or-later). MLX LM is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/khoj-vs-mlx-lm.json, and with the fewest tokens: https://www.anchorterminal.com/compare/khoj-vs-mlx-lm.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"khoj\", \"b\": \"mlx-lm\"}`. From a terminal: `anchor compare khoj mlx-lm`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/khoj.json and https://www.anchorterminal.com/api/v1/tools/mlx-lm.json\n\n## Other comparisons with Khoj or MLX LM\n\n- [AnythingLLM vs Khoj](https://www.anchorterminal.com/compare/anythingllm-vs-khoj.md)\n- [AnythingLLM vs MLX LM](https://www.anchorterminal.com/compare/anythingllm-vs-mlx-lm.md)\n- [Docker Model Runner vs Khoj](https://www.anchorterminal.com/compare/docker-model-runner-vs-khoj.md)\n- [Docker Model Runner vs MLX LM](https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm.md)\n- [Foundry Local vs Khoj](https://www.anchorterminal.com/compare/foundry-local-vs-khoj.md)\n- [Foundry Local vs MLX LM](https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm.md)\n- [Core vs Khoj](https://www.anchorterminal.com/compare/ghost-core-vs-khoj.md)\n- [Core vs MLX LM](https://www.anchorterminal.com/compare/ghost-core-vs-mlx-lm.md)\n- [GPT4All vs Khoj](https://www.anchorterminal.com/compare/gpt4all-vs-khoj.md)\n- [GPT4All vs MLX LM](https://www.anchorterminal.com/compare/gpt4all-vs-mlx-lm.md)\n- [Jan vs Khoj](https://www.anchorterminal.com/compare/jan-vs-khoj.md)\n- [Jan vs MLX LM](https://www.anchorterminal.com/compare/jan-vs-mlx-lm.md)\n- [Khoj vs KoboldCpp](https://www.anchorterminal.com/compare/khoj-vs-koboldcpp.md)\n- [Khoj vs Lemonade](https://www.anchorterminal.com/compare/khoj-vs-lemonade.md)\n- [Khoj vs llama.cpp](https://www.anchorterminal.com/compare/khoj-vs-llama-cpp.md)\n- [Khoj vs LM Studio](https://www.anchorterminal.com/compare/khoj-vs-lm-studio.md)\n- [Khoj vs LocalAI](https://www.anchorterminal.com/compare/khoj-vs-localai.md)\n- [Khoj vs Ollama](https://www.anchorterminal.com/compare/khoj-vs-ollama.md)\n- [Khoj vs Open WebUI](https://www.anchorterminal.com/compare/khoj-vs-open-webui.md)\n- [Khoj vs TextGen](https://www.anchorterminal.com/compare/khoj-vs-text-generation-webui.md)\n- [KoboldCpp vs MLX LM](https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.md)\n- [Lemonade vs MLX LM](https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.md)\n- [llama.cpp vs MLX LM](https://www.anchorterminal.com/compare/llama-cpp-vs-mlx-lm.md)\n- [LM Studio vs MLX LM](https://www.anchorterminal.com/compare/lm-studio-vs-mlx-lm.md)\n- [LocalAI vs MLX LM](https://www.anchorterminal.com/compare/localai-vs-mlx-lm.md)\n- [MLX LM vs Ollama](https://www.anchorterminal.com/compare/mlx-lm-vs-ollama.md)\n- [MLX LM vs Open WebUI](https://www.anchorterminal.com/compare/mlx-lm-vs-open-webui.md)\n- [MLX LM vs screenpipe](https://www.anchorterminal.com/compare/mlx-lm-vs-screenpipe.md)\n- [MLX LM vs TextGen](https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui.md)\n- [MLX LM vs Underdog](https://www.anchorterminal.com/compare/mlx-lm-vs-underdog.md)\n- [Khoj vs LocalGhost](https://www.anchorterminal.com/compare/khoj-vs-localghost.md)\n- [Khoj vs screenpipe](https://www.anchorterminal.com/compare/khoj-vs-screenpipe.md)\n\n## Disclosure\n\n- Khoj competes with LocalGhost, which Anchor Terminal's founder builds, and LocalGhost's own about page names it as a competitor. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.\n",
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