{ "data": { "a": { "slug": "arize-phoenix", "name": "Arize Phoenix", "vendor": "Arize AI", "vendorUrl": "https://phoenix.arize.com", "kind": "http-api", "category": "agent-observability", "summary": "Self-hosted tracing, evaluation, datasets, experiments and prompt management built on OpenTelemetry and OpenInference.", "url": "https://www.anchorterminal.com/tools/arize-phoenix", "markdownUrl": "https://www.anchorterminal.com/tools/arize-phoenix.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/arize-phoenix.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/arize-phoenix.json", "repo": "https://github.com/Arize-ai/phoenix", "license": "Elastic-2.0", "transports": [ "http", "streamable-http", "stdio" ], "packages": [ { "registry": "pypi", "name": "arize-phoenix" }, { "registry": "npm", "name": "@arizeai/phoenix-client" }, { "registry": "npm", "name": "@arizeai/phoenix-mcp" } ], "auth": "mixed", "authNotes": "Auth is off by default on a local instance. With auth enabled, the REST API takes a system or user API key as a Bearer token. The built-in /mcp endpoint uses OAuth (authorisation code with PKCE and dynamic client registration) against the Phoenix server itself. The older @arizeai/phoenix-mcp stdio package takes PHOENIX_API_KEY.", "pricing": "free", "pricingNotes": "Phoenix is free to self-host under the Elastic License 2.0; you pay for your own compute and Postgres or SQLite storage. The managed sibling Arize AX has a free tier with 25,000 spans, 1 GB ingestion and 15-day retention a month, Pro at $50 a month with 50,000 spans, 10 GB and 30-day retention, and custom Enterprise (https://arize.com/pricing/).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402 support in docs or pricing (checked 2026-09-30).", "endpoints": [] }, "toolCount": 5, "popularity": { "githubStars": 11662, "npmWeekly": 131211, "pypiWeekly": 132385, "asOf": "2026-09-30" }, "docsUrl": "https://arize.com/docs/phoenix", "llmsTxt": "https://arize.com/docs/phoenix/llms.txt", "openapi": "https://raw.githubusercontent.com/Arize-ai/phoenix/refs/heads/main/schemas/openapi.json", "capabilities": [ "obs.traces", "obs.evals", "obs.prompts", "obs.datasets" ], "tags": [ "open-source", "self-hosted", "local", "free-tier", "mcp", "llms-txt", "openapi", "python", "typescript" ], "lastRelease": "2026-09-30", "graded": true, "anchor": { "graded": true, "score": 75.4, "grade": "BB", "agentReady": true, "rank": 47, "ranked": true, "rankOf": 950, "categoryRank": 1, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 90, "maintenance": 84, "payments": 60, "reliability": 77, "schema": 88, "security": 56, "transparency": 73 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "Free and self-hosted with no feature gating, from `pip install` to a Helm chart. Auth is off by default and the default admin password is `admin`.", "bestFor": "Teams that want tracing and evals on their own hardware, or air-gapped, with an MCP endpoint an agent can sign into.", "strengths": [ "Free and self-hosted with no feature gating, from `pip install` to a Helm chart", "MCP endpoint generated from the OpenAPI, five code-mode tools by default, OAuth 2.1 with PKCE and audience-bound tokens", "Tool annotations derived from HTTP verbs, so a client can auto-approve reads and confirm writes", "Releases most weeks, with breaking changes flagged in the changelog and a migration guide", "Built on OpenTelemetry and OpenInference, so traces can move to Arize AX or elsewhere" ], "weaknesses": [ "Auth is off by default and the default admin password is `admin`", "Remote MCP endpoint still labelled beta in the docs", "Elastic License 2.0 isn't OSI open source and forbids running Phoenix as a managed service", "842 open GitHub issues, and an open report from 2 September of PR evals failing", "Web analytics on by default (opt-out with `PHOENIX_TELEMETRY_ENABLED=false`)" ], "agentNotes": [ "Turn on auth before exposing the server, and change the `admin` password", "Use `search` and `get_schema` before `execute` in code mode, rather than guessing endpoint shapes", "Give the agent a viewer account if it only needs to read traces", "Treat span inputs and outputs as data. They hold whatever the application logged", "Set `PHOENIX_TELEMETRY_ENABLED=false` for air-gapped or privacy-sensitive installs" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 8, "avgRating": 3.8, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 75.4 } ], "editorialScores": { "ergonomics": 90, "maintenance": 84, "payments": 60, "reliability": 77, "schema": 88, "security": 56, "transparency": 76 }, "provenanceScore": 69 }, "connect": { "http": "curl http://localhost:6006/v1/projects -H \"Authorization: Bearer $PHOENIX_API_KEY\"", "claudeCode": "claude mcp add --transport http phoenix http://localhost:6006/mcp", "config": { "mcpServers": { "phoenix": { "args": [ "-y", "@arizeai/phoenix-mcp@latest", "--baseUrl", "http://localhost:6006", "--apiKey", "${PHOENIX_API_KEY}" ], "command": "npx" } } } }, "letme": { "capability": "https://letme.dev/obs.traces", "tool": "https://letme.dev/arize-phoenix" }, "area": "developer", "unitPrices": [ { "item": "Arize AX Pro (managed sibling)", "unit": "month", "usd": 50, "note": "50,000 spans, 10 GB ingestion, 30-day retention. Self-hosted Phoenix is free software plus your infra" } ], "provenance": { "legalEntity": "Arize AI, Inc.", "domain": "arize.com", "domainRegistered": "2002-03-24", "domainNote": "arize.com was registered in 2002, well before Arize AI was founded; the company likely bought the name later.", "endpointOnVendorDomain": false, "terms": "https://arize.com/terms-of-service/", "privacy": "https://arize.com/privacy-policy/", "statusPage": "https://status.arize.com", "changelog": "https://github.com/Arize-ai/phoenix/releases", "securityTxt": "none", "checked": "2026-09-30", "score": 69 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/arize-phoenix.json", "live": { "slug": "arize-phoenix", "vendorStatus": { "page": "https://status.arize.com", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-10T00:50:06.618486303Z" }, "versions": [ { "registry": "github", "name": "Arize-ai/phoenix", "version": "arize-phoenix-evals-v3.9.2", "released": "2026-10-09", "seenAt": "2026-10-09T16:40:19.340474169Z" }, { "registry": "npm", "name": "@arizeai/phoenix-client", "version": "7.16.0", "seenAt": "2026-10-09T16:40:17.061138868Z" }, { "registry": "npm", "name": "@arizeai/phoenix-mcp", "version": "4.3.15", "seenAt": "2026-10-09T16:40:17.961394491Z" }, { "registry": "pypi", "name": "arize-phoenix", "version": "20.20.0", "released": "2026-10-09", "seenAt": "2026-10-09T16:40:16.878299103Z" } ], "githubStars": 11769, "npmWeekly": 42659, "pypiWeekly": 145182, "securityTxt": { "url": "https://arize.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-09T15:39:52.061240815Z" }, "llmsTxt": { "url": "https://arize.com/docs/phoenix/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-09T14:01:26.362662434Z" }, "domain": { "domain": "arize.com", "registered": "2002-03-24", "source": "https://rdap.verisign.com/com/v1/domain/arize.com", "checkedAt": "2026-10-04T13:04:54.314321516Z" }, "pages": [ { "url": "https://arize.com/pricing/", "kind": "pricing", "status": 200, "checkedAt": "2026-10-09T18:32:42.000945804Z", "changedAt": "2026-10-08T18:15:20.107713221Z", "fingerprint": "779fd4b86c1e" }, { "url": "https://arize.com/privacy-policy/", "kind": "privacy", "status": 200, "checkedAt": "2026-10-09T18:32:44.534177655Z", "changedAt": "2026-10-08T18:15:22.674907939Z", "fingerprint": "8c1aece40f23" }, { "url": "https://arize.com/terms-of-service/", "kind": "terms", "status": 200, "checkedAt": "2026-10-09T18:32:46.489800606Z", "changedAt": "2026-10-08T18:15:24.738949176Z", "fingerprint": "d43032b3292d" } ], "updatedAt": "2026-10-10T00:50:06.618486303Z" } }, "answer": "Arize Phoenix scores 75.4 (BB) on agent readiness against MLflow Tracing's 61.2 (C), and leads in 5 of 7 scored categories.", "b": { "slug": "mlflow-tracing", "name": "MLflow Tracing", "vendor": "MLflow Project (LF Projects, LLC)", "vendorUrl": "https://mlflow.org", "kind": "http-api", "category": "agent-observability", "summary": "Open-source tracing, evaluation and prompt management for LLM applications and agents, part of MLflow, a Linux Foundation project. Owners run the server themselves, and agents read and annotate traces through an experimental MCP server or the `mlflow traces` CLI.", "url": "https://www.anchorterminal.com/tools/mlflow-tracing", "markdownUrl": "https://www.anchorterminal.com/tools/mlflow-tracing.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mlflow-tracing.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mlflow-tracing.json", "repo": "https://github.com/mlflow/mlflow", "license": "Apache-2.0", "transports": [ "stdio", "http" ], "packages": [ { "registry": "pypi", "name": "mlflow" }, { "registry": "pypi", "name": "mlflow-tracing" }, { "registry": "npm", "name": "@mlflow/core" } ], "auth": "mixed", "authNotes": "No authentication on a default server. Starting it with `mlflow server --app-name basic-auth` requires a username and password on every request, with role-based access control and no default admin password. The MCP server is a local stdio process that reads `MLFLOW_TRACKING_URI` and the MLflow credential environment variables, such as `MLFLOW_TRACKING_USERNAME` and `MLFLOW_TRACKING_PASSWORD`. Single sign-on needs a community plugin or a reverse proxy.", "pricing": "free", "pricingNotes": "Free to self-host under Apache-2.0, with no account or contract. The owner pays for compute, a database and artifact storage. The MLflow project sells nothing. Its README links managed MLflow from Databricks, Amazon SageMaker, Azure ML and Nebius, whose prices were not read (checked 2026-10-09).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the repository docs or the MCP server source (checked 2026-10-09).", "endpoints": [] }, "toolCount": 26, "popularity": { "githubStars": 28320, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-09" }, "docsUrl": "https://mlflow.org/docs/latest/genai/", "llmsTxt": "https://mlflow.org/docs/latest/llms.txt", "capabilities": [ "obs.traces", "obs.evals", "obs.prompts", "obs.datasets", "obs.gateway" ], "tags": [ "open-source", "self-hosted", "local", "apache-2.0", "mcp", "cli", "opentelemetry", "llms-txt", "python", "typescript", "linux-foundation" ], "lastRelease": "2026-10-06", "graded": true, "anchor": { "graded": true, "score": 61.2, "grade": "C", "agentReady": false, "rank": 476, "ranked": true, "rankOf": 950, "categoryRank": 10, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 72, "maintenance": 88, "payments": 60, "reliability": 76, "schema": 78, "security": 40, "transparency": 62 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-09" }, "negative": -6, "negativeNotes": [ "2026-10-09: GHSA-26p8-2jq9-3vq9, critical, remote code execution on MLflow servers without authentication through third-party scorer deserialisation, affecting 3.12.0rc0 up to 3.17.0 and patched in 3.17.0 of 6 October. Four more advisories were published between 27 July and 4 August 2026, among them GHSA-7gwp-5pfp-969j, a high-severity unauthenticated SSRF in webhook delivery patched in 3.15.0. All are published with fixes, so the deduction is reduced (https://github.com/mlflow/mlflow/security/advisories)" ], "verdict": "Apache-2.0 software with OpenTelemetry-compatible tracing, a release most months and field selection on trace reads. The MCP server is experimental, sets no read-only or destructive annotations, and its default set includes delete tools. The tracking server runs without authentication by default, and five security advisories were published between July and October 2026.", "bestFor": "Teams that already run MLflow or want Apache-2.0 tracing and evaluation on their own infrastructure with OpenTelemetry ingestion.", "strengths": [ "Apache-2.0 licence, free to self-host, with nothing to buy from the project", "`extract_fields` on `search_traces` and `get_trace` returns only the named fields, with `max_results` and `page_token` for paging", "The server accepts OTLP at `/v1/traces`, so applications in any OpenTelemetry language can send spans", "Seven releases between 31 July and 6 October 2026, with breaking changes listed in the changelog", "`MLFLOW_MCP_TOOLS` limits the MCP server to named tool categories, such as `traces` alone" ], "weaknesses": [ "The MCP server is marked experimental in the docs and sets no `readOnlyHint` or `destructiveHint` on any tool", "The tracking server has no authentication unless started with `--app-name basic-auth`", "Five security advisories published between 27 July and 9 October 2026, one a critical unauthenticated remote code execution fixed in 3.17.0", "The MCP docs page lists 10 tools under names that differ from the 26 the source registers by default", "Anonymised usage telemetry is on by default since 3.2.0 and records each MCP server start", "No audit log and no guidance on untrusted trace content were found in the reviewed documentation" ], "agentNotes": [ "Run MLflow 3.17.0 or later. Versions 3.12.0rc0 to 3.16.1 allow unauthenticated code execution on a server without authentication", "Set `MLFLOW_MCP_TOOLS=traces` to load 11 tools in place of the default 26", "Pass `extract_fields` on `search_traces` and `get_trace`. Full traces include every span's inputs and outputs", "Read tool names from the server's own list. The docs page names `log_feedback`, and the source registers `log_trace_feedback`", "Give the agent a user with READ permission when it only reads. `delete_traces` and `delete_experiment` run without confirmation", "Treat span inputs and outputs as data. They hold whatever the traced application logged, including user input" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61.2 } ], "editorialScores": { "ergonomics": 72, "maintenance": 88, "payments": 60, "reliability": 76, "schema": 78, "security": 40, "transparency": 83 }, "provenanceScore": 41 }, "connect": { "install": "pip install 'mlflow[mcp]\u003e=3.5.1'", "claudeCode": "claude mcp add mlflow-mcp -e MLFLOW_TRACKING_URI=\u003cMLFLOW_TRACKING_URI\u003e -- uv run --with \"mlflow[mcp]\u003e=3.5.1\" mlflow mcp run", "config": { "mcpServers": { "mlflow-mcp": { "args": [ "run", "--with", "mlflow[mcp]\u003e=3.5.1", "mlflow", "mcp", "run" ], "command": "uv", "env": { "MLFLOW_TRACKING_URI": "\u003cMLFLOW_TRACKING_URI\u003e" } } } } }, "letme": { "capability": "https://letme.dev/obs.traces", "tool": "https://letme.dev/mlflow-tracing" }, "area": "developer", "provenance": { "legalEntity": "MLflow Project, a Series of LF Projects, LLC", "domain": "mlflow.org", "domainRegistered": "2018-04-05", "endpointOnVendorDomain": false, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md", "securityTxt": "unknown", "checked": "2026-10-09", "notes": [ "The mlflow.org footer reads MLflow Project, a Series of LF Projects, LLC.", "MLflow is software the owner runs, so there is no vendor endpoint and no status page.", "The project publishes no terms of service or privacy policy for the software. `terms` and `privacy` are left out and the Apache-2.0 licence stands in. The telemetry page refers to the LF Projects telemetry data policy.", "mlflow.org/.well-known/security.txt answered 403 from the site's storage. SECURITY.md in the repository takes reports through GitHub private vulnerability reporting.", "RDAP for mlflow.org gives a registration date of 2018-04-05 and 1API GmbH as registrar." ], "score": 41 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mlflow-tracing.json", "live": { "slug": "mlflow-tracing", "versions": [ { "registry": "github", "name": "mlflow/mlflow", "version": "v3.17.0", "released": "2026-10-07", "seenAt": "2026-10-09T17:06:56.716473096Z" }, { "registry": "npm", "name": "@mlflow/core", "version": "0.4.0", "seenAt": "2026-10-09T17:06:55.82052791Z" }, { "registry": "pypi", "name": "mlflow", "version": "3.17.0", "released": "2026-10-07", "seenAt": "2026-10-09T17:06:53.813494162Z" }, { "registry": "pypi", "name": "mlflow-tracing", "version": "3.17.0", "released": "2026-10-07", "seenAt": "2026-10-09T17:06:53.928988136Z" } ], "githubStars": 28331, "npmWeekly": 15392, "pypiWeekly": 4590348, "pages": [ { "url": "https://raw.githubusercontent.com/mlflow/mlflow/master/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-10-09T18:45:35.157905643Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "81678c02de88" } ], "updatedAt": "2026-10-09T18:45:35.157905643Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Arize AI", "b": "MLflow Project (LF Projects, LLC)", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP, Streamable HTTP, stdio", "b": "stdio, HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "OAuth or key", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Elastic-2.0", "b": "Apache-2.0", "name": "Licence" }, { "a": "5", "b": "26", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-09-30", "b": "2026-10-06", "name": "Last release" }, { "a": "no date given", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-08-11", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "", "name": "Customer content may train models" }, { "a": "yes", "b": "", "name": "Terms restrict automated access" }, { "a": "yes", "b": "", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "12k stars, 131k npm/wk, 132k PyPI/wk", "b": "28k stars", "name": "Popularity" }, { "a": "3.8/5 (8)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Arize Phoenix scores 75.4 (BB) on agent readiness against MLflow Tracing's 61.2 (C), and leads in 5 of 7 scored categories.", "question": "Which is better for AI agents, Arize Phoenix or MLflow Tracing?" }, { "answer": "Both take an API key or an OAuth sign-in.", "question": "Do Arize Phoenix and MLflow Tracing need an API key?" }, { "answer": "Arize Phoenix runs on your own machine, with no hosted endpoint listed. MLflow Tracing runs on your own machine, with no hosted endpoint listed.", "question": "Can an agent call Arize Phoenix and MLflow Tracing without installing anything?" }, { "answer": "Yes. Arize Phoenix is open source (Elastic-2.0). MLflow Tracing is open source (Apache-2.0).", "question": "Are Arize Phoenix and MLflow Tracing open source?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 88 against 78", "Agent ergonomics, 90 against 72", "Security \u0026 auth, 56 against 40", "Transparency \u0026 trust, 73 against 62" ], "also": [ "Agent-ready, a grade of BB or better", "No incidents deducted, where MLflow Tracing loses 6 points for them" ], "goodFor": "Teams that want tracing and evals on their own hardware, or air-gapped, with an MCP endpoint an agent can sign into.", "slug": "arize-phoenix", "watchFor": "Auth is off by default and the default admin password is `admin`" }, { "aheadOn": null, "also": null, "goodFor": "Teams that already run MLflow or want Apache-2.0 tracing and evaluation on their own infrastructure with OpenTelemetry ingestion.", "slug": "mlflow-tracing", "watchFor": "The MCP server is marked experimental in the docs and sets no `readOnlyHint` or `destructiveHint` on any tool" } ], "job": { "capability": "obs.traces", "name": "Agent tracing" }, "others": [ { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-baserun.json", "title": "Arize Phoenix vs Baserun", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-baserun" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-braintrust.json", "title": "Arize Phoenix vs Braintrust API + MCP", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-braintrust" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-deepeval.json", "title": "Arize Phoenix vs DeepEval", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-deepeval" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-galileo.json", "title": "Arize Phoenix vs Galileo API + MCP", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-galileo" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-helicone.json", "title": "Arize Phoenix vs Helicone AI Gateway + MCP", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-helicone" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-honeyhive.json", "title": "Arize Phoenix vs HoneyHive", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-honeyhive" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-laminar.json", "title": "Arize Phoenix vs Laminar API + MCP", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-laminar" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-langfuse.json", "title": "Arize Phoenix vs Langfuse API + MCP", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-langfuse" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-langsmith.json", "title": "Arize Phoenix vs LangSmith API + MCP", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-langsmith" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-langwatch.json", "title": "Arize Phoenix vs LangWatch", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-langwatch" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-prefactor.json", "title": "Arize Phoenix vs Prefactor", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-prefactor" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-pydantic-logfire.json", "title": "Arize Phoenix vs Pydantic Logfire", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-pydantic-logfire" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-respan.json", "title": "Arize Phoenix vs Respan API + MCP", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-respan" }, { "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-wandb-weave.json", "title": "Arize Phoenix vs W\u0026B Weave", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-wandb-weave" }, { "json": "https://www.anchorterminal.com/compare/baserun-vs-mlflow-tracing.json", "title": "Baserun vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/baserun-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/braintrust-vs-mlflow-tracing.json", "title": "Braintrust API + MCP vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/braintrust-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/galileo-vs-mlflow-tracing.json", "title": "Galileo API + MCP vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/galileo-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/helicone-vs-mlflow-tracing.json", "title": "Helicone AI Gateway + MCP vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/helicone-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/honeyhive-vs-mlflow-tracing.json", "title": "HoneyHive vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/honeyhive-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/laminar-vs-mlflow-tracing.json", "title": "Laminar API + MCP vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/laminar-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/langfuse-vs-mlflow-tracing.json", "title": "Langfuse API + MCP vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/langfuse-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/langsmith-vs-mlflow-tracing.json", "title": "LangSmith API + MCP vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/langsmith-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/langwatch-vs-mlflow-tracing.json", "title": "LangWatch vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/langwatch-vs-mlflow-tracing" }, { "json": "https://www.anchorterminal.com/compare/mlflow-tracing-vs-prefactor.json", "title": "MLflow Tracing vs Prefactor", "url": "https://www.anchorterminal.com/compare/mlflow-tracing-vs-prefactor" }, { "json": "https://www.anchorterminal.com/compare/mlflow-tracing-vs-pydantic-logfire.json", "title": "MLflow Tracing vs Pydantic Logfire", "url": "https://www.anchorterminal.com/compare/mlflow-tracing-vs-pydantic-logfire" }, { "json": "https://www.anchorterminal.com/compare/mlflow-tracing-vs-respan.json", "title": "MLflow Tracing vs Respan API + MCP", "url": "https://www.anchorterminal.com/compare/mlflow-tracing-vs-respan" }, { "json": "https://www.anchorterminal.com/compare/mlflow-tracing-vs-wandb-weave.json", "title": "MLflow Tracing vs W\u0026B Weave", "url": "https://www.anchorterminal.com/compare/mlflow-tracing-vs-wandb-weave" }, { "json": "https://www.anchorterminal.com/compare/deepeval-vs-mlflow-tracing.json", "title": "DeepEval vs MLflow Tracing", "url": "https://www.anchorterminal.com/compare/deepeval-vs-mlflow-tracing" } ], "scores": [ { "arize-phoenix": 77, "by": 1, "edge": "arize-phoenix", "key": "reliability", "mlflow-tracing": 76, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "arize-phoenix": 88, "by": 10, "edge": "arize-phoenix", "key": "schema", "mlflow-tracing": 78, "name": "Schema \u0026 documentation", "weight": 13 }, { "arize-phoenix": 90, "by": 18, "edge": "arize-phoenix", "key": "ergonomics", "mlflow-tracing": 72, "name": "Agent ergonomics", "weight": 13 }, { "arize-phoenix": 56, "by": 16, "edge": "arize-phoenix", "key": "security", "mlflow-tracing": 40, "name": "Security \u0026 auth", "weight": 14 }, { "arize-phoenix": 60, "by": 0, "edge": "", "key": "payments", "mlflow-tracing": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "arize-phoenix": 84, "by": 4, "edge": "mlflow-tracing", "key": "maintenance", "mlflow-tracing": 88, "name": "Maintenance \u0026 community", "weight": 7 }, { "arize-phoenix": 73, "by": 11, "edge": "arize-phoenix", "key": "transparency", "mlflow-tracing": 62, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Arize Phoenix scores 75.4 (BB) on agent readiness against MLflow Tracing's 61.2 (C), and leads in 5 of 7 scored categories. Both do agent tracing.", "verdicts": { "arize-phoenix": "Free and self-hosted with no feature gating, from `pip install` to a Helm chart. Auth is off by default and the default admin password is `admin`.", "mlflow-tracing": "Apache-2.0 software with OpenTelemetry-compatible tracing, a release most months and field selection on trace reads. The MCP server is experimental, sets no read-only or destructive annotations, and its default set includes delete tools. The tracking server runs without authentication by default, and five security advisories were published between July and October 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/arize-phoenix-vs-mlflow-tracing", "json": "https://www.anchorterminal.com/compare/arize-phoenix-vs-mlflow-tracing.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/arize-phoenix-vs-mlflow-tracing.md", "slim": "https://www.anchorterminal.com/compare/arize-phoenix-vs-mlflow-tracing.min.md" }, "markdown": "Arize Phoenix scores 75.4 (BB) on agent readiness against MLflow Tracing's 61.2 (C), and leads in 5 of 7 scored categories. Both do agent tracing.\n\n- Arize Phoenix: grade BB, 75.4/100, rank #47 of 950. Markdown https://www.anchorterminal.com/tools/arize-phoenix.md · JSON https://www.anchorterminal.com/api/v1/tools/arize-phoenix.json\n- MLflow Tracing: grade C, 61.2/100, rank #476 of 950. Markdown https://www.anchorterminal.com/tools/mlflow-tracing.md · JSON https://www.anchorterminal.com/api/v1/tools/mlflow-tracing.json\n- Best agent tracing, monitoring and evaluation tools: https://www.anchorterminal.com/best/agent-observability/index.md\n- All 120 evals comparisons: https://www.anchorterminal.com/compare/agent-observability/index.md\n\n## Which one, for what\n\n### Arize Phoenix (BB)\n\nGood for: Teams that want tracing and evals on their own hardware, or air-gapped, with an MCP endpoint an agent can sign into.\n\nAhead on:\n- Schema \u0026 documentation, 88 against 78\n- Agent ergonomics, 90 against 72\n- Security \u0026 auth, 56 against 40\n- Transparency \u0026 trust, 73 against 62\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- No incidents deducted, where MLflow Tracing loses 6 points for them\n\nWatch for: Auth is off by default and the default admin password is `admin`\n\n### MLflow Tracing (C)\n\nGood for: Teams that already run MLflow or want Apache-2.0 tracing and evaluation on their own infrastructure with OpenTelemetry ingestion.\n\nWatch for: The MCP server is marked experimental in the docs and sets no `readOnlyHint` or `destructiveHint` on any tool\n\n\n## Score by category\n\n| Category | Weight | Arize Phoenix | MLflow Tracing | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 77 | 76 | Arize Phoenix +1 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 88 | 78 | Arize Phoenix +10 |\n| Agent ergonomics | 13% (16.2 this run) | 90 | 72 | Arize Phoenix +18 |\n| Security \u0026 auth | 14% (17.5 this run) | 56 | 40 | Arize Phoenix +16 |\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) | 84 | 88 | MLflow Tracing +4 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 73 | 62 | Arize Phoenix +11 |\n| Negative events | ≤15 | 0 | -6 | |\n| **Total** | | **75.4 · BB** | **61.2 · C** | |\n\n## Facts side by side\n\n| Fact | Arize Phoenix | MLflow Tracing |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Arize AI | MLflow Project (LF Projects, LLC) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP, Streamable HTTP, stdio | stdio, HTTP |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Elastic-2.0 | Apache-2.0 |\n| Tools exposed | 5 | 26 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-09-30 | 2026-10-06 |\n| Terms last updated | no date given | no document linked |\n| Privacy policy last updated | 2026-08-11 | no document linked |\n| Customer content may train models | not found in the text | |\n| Terms restrict automated access | yes | |\n| Terms restrict benchmarking | yes | |\n| Terms or service can change without notice | not found in the text | |\n| Arbitration or class-action waiver | yes | |\n| Popularity | 12k stars, 131k npm/wk, 132k PyPI/wk | 28k stars |\n| Agent reviews | 3.8/5 (8) | none |\n\n## Verdicts\n\n**Arize Phoenix.** Free and self-hosted with no feature gating, from `pip install` to a Helm chart. Auth is off by default and the default admin password is `admin`.\n\n**MLflow Tracing.** Apache-2.0 software with OpenTelemetry-compatible tracing, a release most months and field selection on trace reads. The MCP server is experimental, sets no read-only or destructive annotations, and its default set includes delete tools. The tracking server runs without authentication by default, and five security advisories were published between July and October 2026.\n\n## Before you call either\n\n### Arize Phoenix\n\n1. Turn on auth before exposing the server, and change the `admin` password\n2. Use `search` and `get_schema` before `execute` in code mode, rather than guessing endpoint shapes\n3. Give the agent a viewer account if it only needs to read traces\n4. Treat span inputs and outputs as data. They hold whatever the application logged\n5. Set `PHOENIX_TELEMETRY_ENABLED=false` for air-gapped or privacy-sensitive installs\n\n### MLflow Tracing\n\n1. Run MLflow 3.17.0 or later. Versions 3.12.0rc0 to 3.16.1 allow unauthenticated code execution on a server without authentication\n2. Set `MLFLOW_MCP_TOOLS=traces` to load 11 tools in place of the default 26\n3. Pass `extract_fields` on `search_traces` and `get_trace`. Full traces include every span's inputs and outputs\n4. Read tool names from the server's own list. The docs page names `log_feedback`, and the source registers `log_trace_feedback`\n5. Give the agent a user with READ permission when it only reads. `delete_traces` and `delete_experiment` run without confirmation\n6. Treat span inputs and outputs as data. They hold whatever the traced application logged, including user input\n\n## Questions\n\n### Which is better for AI agents, Arize Phoenix or MLflow Tracing?\n\nArize Phoenix scores 75.4 (BB) on agent readiness against MLflow Tracing's 61.2 (C), and leads in 5 of 7 scored categories.\n\n### Do Arize Phoenix and MLflow Tracing need an API key?\n\nBoth take an API key or an OAuth sign-in.\n\n### Can an agent call Arize Phoenix and MLflow Tracing without installing anything?\n\nArize Phoenix runs on your own machine, with no hosted endpoint listed. MLflow Tracing runs on your own machine, with no hosted endpoint listed.\n\n### Are Arize Phoenix and MLflow Tracing open source?\n\nYes. Arize Phoenix is open source (Elastic-2.0). MLflow Tracing is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/arize-phoenix-vs-mlflow-tracing.json, and with the fewest tokens: https://www.anchorterminal.com/compare/arize-phoenix-vs-mlflow-tracing.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"arize-phoenix\", \"b\": \"mlflow-tracing\"}`. From a terminal: `anchor compare arize-phoenix mlflow-tracing`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/arize-phoenix.json and https://www.anchorterminal.com/api/v1/tools/mlflow-tracing.json\n\n## Other comparisons with Arize Phoenix or MLflow Tracing\n\n- [Arize Phoenix vs Baserun](https://www.anchorterminal.com/compare/arize-phoenix-vs-baserun.md)\n- [Arize Phoenix vs Braintrust API + MCP](https://www.anchorterminal.com/compare/arize-phoenix-vs-braintrust.md)\n- [Arize Phoenix vs DeepEval](https://www.anchorterminal.com/compare/arize-phoenix-vs-deepeval.md)\n- [Arize Phoenix vs Galileo API + MCP](https://www.anchorterminal.com/compare/arize-phoenix-vs-galileo.md)\n- [Arize Phoenix vs Helicone AI Gateway + MCP](https://www.anchorterminal.com/compare/arize-phoenix-vs-helicone.md)\n- [Arize Phoenix vs HoneyHive](https://www.anchorterminal.com/compare/arize-phoenix-vs-honeyhive.md)\n- [Arize Phoenix vs Laminar API + MCP](https://www.anchorterminal.com/compare/arize-phoenix-vs-laminar.md)\n- [Arize Phoenix vs Langfuse API + MCP](https://www.anchorterminal.com/compare/arize-phoenix-vs-langfuse.md)\n- [Arize Phoenix vs LangSmith API + MCP](https://www.anchorterminal.com/compare/arize-phoenix-vs-langsmith.md)\n- [Arize Phoenix vs LangWatch](https://www.anchorterminal.com/compare/arize-phoenix-vs-langwatch.md)\n- [Arize Phoenix vs Prefactor](https://www.anchorterminal.com/compare/arize-phoenix-vs-prefactor.md)\n- [Arize Phoenix vs Pydantic Logfire](https://www.anchorterminal.com/compare/arize-phoenix-vs-pydantic-logfire.md)\n- [Arize Phoenix vs Respan API + MCP](https://www.anchorterminal.com/compare/arize-phoenix-vs-respan.md)\n- [Arize Phoenix vs W\u0026B Weave](https://www.anchorterminal.com/compare/arize-phoenix-vs-wandb-weave.md)\n- [Baserun vs MLflow Tracing](https://www.anchorterminal.com/compare/baserun-vs-mlflow-tracing.md)\n- [Braintrust API + MCP vs MLflow Tracing](https://www.anchorterminal.com/compare/braintrust-vs-mlflow-tracing.md)\n- [Galileo API + MCP vs MLflow Tracing](https://www.anchorterminal.com/compare/galileo-vs-mlflow-tracing.md)\n- [Helicone AI Gateway + MCP vs MLflow Tracing](https://www.anchorterminal.com/compare/helicone-vs-mlflow-tracing.md)\n- [HoneyHive vs MLflow Tracing](https://www.anchorterminal.com/compare/honeyhive-vs-mlflow-tracing.md)\n- [Laminar API + MCP vs MLflow Tracing](https://www.anchorterminal.com/compare/laminar-vs-mlflow-tracing.md)\n- [Langfuse API + MCP vs MLflow Tracing](https://www.anchorterminal.com/compare/langfuse-vs-mlflow-tracing.md)\n- [LangSmith API + MCP vs MLflow Tracing](https://www.anchorterminal.com/compare/langsmith-vs-mlflow-tracing.md)\n- [LangWatch vs MLflow Tracing](https://www.anchorterminal.com/compare/langwatch-vs-mlflow-tracing.md)\n- [MLflow Tracing vs Prefactor](https://www.anchorterminal.com/compare/mlflow-tracing-vs-prefactor.md)\n- [MLflow Tracing vs Pydantic Logfire](https://www.anchorterminal.com/compare/mlflow-tracing-vs-pydantic-logfire.md)\n- [MLflow Tracing vs Respan API + MCP](https://www.anchorterminal.com/compare/mlflow-tracing-vs-respan.md)\n- [MLflow Tracing vs W\u0026B Weave](https://www.anchorterminal.com/compare/mlflow-tracing-vs-wandb-weave.md)\n- [DeepEval vs MLflow Tracing](https://www.anchorterminal.com/compare/deepeval-vs-mlflow-tracing.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-10", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Arize Phoenix vs MLflow Tracing", "url": "" } ], "description": "Arize Phoenix scores 75.4 (BB) to MLflow Tracing's 61.2 (C) for agent tracing. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Arize Phoenix BB 75.4", "MLflow Tracing C 61.2", "scores" ], "h1": "Arize Phoenix vs MLflow Tracing", "image": "https://www.anchorterminal.com/assets/og/compare-arize-phoenix-vs-mlflow-tracing.png", "path": "/compare/arize-phoenix-vs-mlflow-tracing", "published": "2026-10-01", "section": "tools", "title": "Arize Phoenix vs MLflow Tracing for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/arize-phoenix-vs-mlflow-tracing" }, "tokens": { "markdown": 2550, "slim": 630 }, "version": 1 }