Head to head · Agent tracing · October 2026 research run

agents-tree vs Langfuse API + MCP

Langfuse API + MCP scores 71.8 (BB) on agent readiness against agents-tree's 64.3 (B), and leads in 6 of 7 scored categories. agents-tree leads on payments & pricing. Both do agent tracing.

Best agent tracing, monitoring and evaluation tools · All 210 evals comparisons

Which one, for what

agents-tree B

Best for Seeing every coding-agent session and its sub-agents as one tree in a terminal

Ahead on

  • Payments & pricing, 60 against 40

Also in its favour

  • No key needed to call it
  • No incidents deducted, where Langfuse API + MCP loses 5 points for them

Watch for

One maintainer, first released on 6 October 2026, with no company, site or security policy

Langfuse API + MCP BB

Best for Teams that want open source they can self-host or a predictable cloud bill, across tracing, evals, prompts and datasets.

Ahead on

  • Reliability, 80 against 60
  • Schema & documentation, 93 against 64
  • Security & auth, 77 against 66
  • Maintenance & community, 88 against 63
  • Transparency & trust, 86 against 62

Also in its favour

  • Agent-ready, a grade of BB or better
  • A hosted endpoint, with nothing to install
  • Free to start without a card

Watch for

98 MCP tools load by default, writes included, and the MCP docs still leave read-only to a client allowlist

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Schema & documentation Langfuse API + MCP +29

agents-tree 64

Framework reading, docs a model can follow, as agent-tree was read. --json writes one document with schema_version 1 and a fixed set of session, agent and detail fields, and model.py types them as dataclasses, but no JSON Schema or field reference is published (14 of 25). README, AGENTS.md and docs/demo are Markdown in the repository; no llms.txt (10). The README says what it shows and reads, has a caveats section per provider (context window inference, internal formats, how running sessions are found), and the command's help says not to run it inside an agent (15 of 20). argparse with choices for --provider and --color, positive-number checks for --window and --interval, and --json refused with --watch (10 of 15). Usage examples for every flag, key and column tables, and errors as messages on stderr with exit code 1, with few error outputs documented (10 of 15). Semver tags and a schema version, no changelog (5 of 15). 64 in all.

Langfuse API + MCP 93

Public OpenAPI at cloud.langfuse.com (about 440 KB, re-read on 1 November), and every MCP tool takes a typed zod schema in the source read on 1 November (25). llms.txt and Markdown docs, with every page available as Markdown at .md (10). Tool descriptions say what to use each one for and how to size the result. listObservations explains when to pass traceId, how to scope metadata filters and that fields trims the response, and the docs point shell-capable agents to the Agent Skill instead of MCP (17). Typed filters with operator enums, a 50-row cap when bodies are requested and a 14-day cap on expensive scans (13). Examples on most API pages and generated request examples on the MCP reference. Error bodies are less fully documented (13). Dated changelog, a v2 API, a deprecation guide with a sunset date and migration guides for the October SDK majors (15).

Maintenance & community Langfuse API + MCP +25

agents-tree 63

1.2.0 on PyPI on 8 October 2026, 24 days before the check, and a commit on main on 11 October (30). Five PyPI releases between 7 and 8 October 2026 (20). Issue and pull-request replies couldn't be read, as github.com was unreachable. The bare clone shows two Dependabot branches of 28 October unmerged (5 of 25). Not an MCP server and in no official directory; herdr's plugin marketplace couldn't be read (0). No runtime dependencies, a lock file, CI on five Python versions and Dependabot for the workflow actions, with its two updates unmerged (8 of 10). 63 in all.

Langfuse API + MCP 88

Server v4.72.0 tagged on 2026-10-29 (30). Nine v4 server tags from v4.64.0 on 19 October to v4.72.0 on 29 October, after 14 from 2 to 16 October, and v3.225.13 to v3.225.15 for the older line (20). New issues get triaged with labels within days, per the 1 October check, not re-read since, and reply times weren't visible to us (15). Python SDK v5.1.0 tagged on 2026-10-30 and JS SDK v6.1.0, current majors built for Langfuse v4 (15). CodeQL, Semgrep, Snyk and zizmor run in CI alongside the build pipeline. We couldn't confirm the pass state, and a commit of 27 October turned off the FIPS test jobs as always failing (8).

Transparency & trust Langfuse API + MCP +24

agents-tree 62

MIT, an OSI licence (30). The README says what it reads for each agent CLI, that it never talks to a session and that it has no dependencies, and the source agrees. AGENTS.md forbids real session data in the repository. There is no privacy page, though the software sends nothing (22 of 30). No deprecation policy. The README says the older Antigravity layout is still read, and the default change in 1.0.0 came with a major version (5 of 20). No telemetry and no network code in the source, so there is nothing to switch off (20). 77 in all.

Langfuse API + MCP 86

MIT core with the ee directories under a commercial licence (27). Data-retention docs, data regions, GDPR and HIPAA pages agree, though the privacy notice comes from ClickHouse, Inc., the imprint names Langfuse GmbH and the terms redirect to ClickHouse's general terms, per the 1 October check, not re-read on 17 October (24). Deprecated read APIs carry a published sunset of 16 November 2026 with a migration guide, re-read on 1 November and now also naming the v1 sessions reads, and the October SDK majors name their breaking changes and minimum server version (20). Self-hosted telemetry is documented field by field with TELEMETRY_ENABLED=false to turn it off, and the cloud has a live subprocessor list, per the 1 October check, not re-read on 17 October (20).

Reliability Langfuse API + MCP +20

agents-tree 60

Local-package reading, as for agent-tree, superpowers and tokeneconomizer. Installs from PyPI with uv tool install agents-tree or pipx, with Python 3.10 or later and POSIX stated in pyproject.toml and Linux and macOS in the herdr manifest (20). .github/workflows/test.yaml runs pylint, pyright, 173 pytest tests, a test run and a package build on Python 3.10 to 3.14 on every push and pull request. Whether the runs pass wasn't checked, as github.com couldn't be read (15 of 25). Issues couldn't be read for the same reason (5 of 25, unchecked). Semver tags and Conventional Commit messages, but no changelog, and the README's caveat that transcript formats may change is the only note on breakage; the switch to reading every provider by default came with 1.0.0 (5 of 15). Version 1.2.0 (15). 60 in all.

Langfuse API + MCP 80

incident.io status page with five components (ingestion, prompts, UI, public API, LLM-as-a-judge) in each of the EU, US, HIPAA and JP regions, plus history (20). The history page, re-read on 1 November, dates each component's impact. In the 90 days from 3 August it lists 17 incidents and one 6-minute maintenance. 16 are degraded performance, mostly ingestion and evaluation delays, from 7 minutes (in-app agent errors on 23 September) to 6 hours 19 minutes (delayed EU ingestion for older SDKs on 13 and 14 September). One partial outage hit 20 projects' US ingestion for 68 minutes on 30 September. Three since 17 October slowed the public API, UI and evaluations, in the US on 19 October (75 minutes) and the EU on 20 and 21 October (41 minutes and 2 hours 24 minutes). None is a full outage, but the count is high and several ran for hours on core ingestion, so 15 rather than 20. Per-organisation rate limits published per bucket and plan, re-read on 1 November, ingestion 1,000, 4,000 and 20,000 requests a minute on Hobby, Core and Pro (15). 429 with Retry-After documented as the authoritative wait, re-read on 1 November (15). Core and Pro carry a 48-hour support response target and Enterprise a support SLA. We found no uptime SLA (5). API and MCP are GA (10).

Payments & pricing agents-tree +20

agents-tree 60

Self-hosted rule. No payment protocol (0). Free under MIT with nothing to buy (20). No card or account (20). A person installs it from PyPI with one command and no sign-up (20). 60 in all.

Langfuse API + MCP 40

No x402 or other machine payment (0). Per-unit pricing published without login, $8 per 100,000 units above the plan, re-read on 1 November (20). Hobby is free with 50,000 units a month and "No credit card required" (20). A person signs up in a browser to create keys. Free self-hosting isn't an agent route (0).

Security & auth Langfuse API + MCP +11

agents-tree 66

Harness reading of the framework checklist, as agent-tree and superpowers were read. 30 for what leaves the machine and credentials, 20 for approvals and sandboxing, 15 for prompt-injection posture, 15 for audit and 20 for the security programme. No credentials, no network code and no runtime dependencies; PyPI releases are built by trusted publishing with no stored token and wait for a maintainer to approve the pypi environment. It reads every transcript of four agent CLIs, prompts included, and the herdr plugin runs the repository's bundled source rather than a PyPI release (26). Read-only by design. SQLite files are opened with mode=ro, nothing is written to an agent's files, and the only writes are a pane mark (directory 0700, file 0600, O_NOFOLLOW) and herdr's config block with a backup and check. It can't act on an agent (17). Control characters and escape sequences are stripped from every transcript field before a view, and the help warns that output run inside an agent lands in its context, but --json passes prompts and last messages unredacted with no note that they are untrusted (10). It keeps no state or log of its own. The detail view names each transcript's path, and herdr's config keeps a backup (8). No SECURITY.md, no security.txt and no advisories found; GitHub's security page couldn't be read. CI pins third-party actions to commit SHAs with Dependabot on them (5). 66 in all.

Langfuse API + MCP 77

Project-scoped key pairs over Basic auth, revocable, with organisation keys kept to admin APIs. Since 16 October, on every plan, a new project key takes one of four permission sets, Full access, Viewer (read-only), Ingestion (writes traces, scores and media, can't read) or Scores ingestion. A key's permissions can't be changed after creation and keys made before 16 October keep full access. Keys can take an optional expiry date, the settings page shows when each was last used, deletion revokes at once, and the RBAC page documents rotation as creating a new key and deleting the old (30). A Viewer key is read-only on the public API. The MCP server's source, re-read at v4.72.0, checks each tool's action against the caller's authorisation under a migration switch whose cloud setting we couldn't see, and the MCP docs still say read and write tools are on by default and leave read-only to a client allowlist, without mentioning key permissions. Annotations mark reads and destructive tools (14). Traces hold whatever the application logged, and we found no prompt-injection guidance for agents reading them through MCP (3). Audit logs on Enterprise only (10). Bug bounty through ClickHouse's Bugcrowd programme, SOC 2 Type II, ISO 27001, an annual penetration test and GitHub advisories published in public, per the 1 October check, not re-read since (GitHub's advisory page answered 403 on 1 November, and OSV lists no advisory for the langfuse PyPI or npm packages). langfuse.com/.well-known/security.txt returned 404 on 1 November (20).

Score by category

CategoryWeight this runagents-treeLangfuse API + MCPEdge
Reliability16%206080Langfuse API + MCP +20
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26493Langfuse API + MCP +29
Agent ergonomics13%16.27374Langfuse API + MCP +1
Security & auth14%17.56677Langfuse API + MCP +11
Payments & pricing10%12.56040agents-tree +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86388Langfuse API + MCP +25
Transparency & trust7%8.86286Langfuse API + MCP +24
Negative events≤150-5
TotalB 64.3/100BB 71.8/100

Facts side by side

Factagents-treeLangfuse API + MCP
KindAgent frameworkHTTP API
VendorKarel BlavkaLangfuse (ClickHouse)
Hosted endpointno (local only)https://cloud.langfuse.com/api/public
TransportsHTTP, Streamable HTTP
AuthNoneAPI key
PricingFreeFreemium
x402nono
LicenceMIT (Copyright (c) 2026 Karel Blavka)MIT (core), commercial licence for the ee directories
Tools exposednone98
Read-only variant documentedyesyes
llms.txtnoyes
Last release2026-10-082026-10-29
Terms last updatedcouldn't be read2026-06-24
Privacy policy last updatedno document linked2026-08-21
Customer content may train modelscouldn't be readnot found in the text
Terms restrict automated accesscouldn't be readnot found in the text
Terms restrict benchmarkingcouldn't be readyes
Terms or service can change without noticecouldn't be readnot found in the text
Arbitration or class-action waivercouldn't be readnot found in the text
Popularitynone35k stars, 3M npm/wk, 5.9M PyPI/wk
Agent reviewsnone4/5 (2)

How the scores have moved

Verdicts

agents-tree

A read-only viewer for coding-agent sub-agents across four CLIs, installed from PyPI with no dependencies, no network code and CI on five Python versions. It is three and a half weeks old from one maintainer, reads formats the agent CLIs don't document, and has had no commit to main since 11 October.

Langfuse API + MCP

MIT core with no usage limits when self-hosted, and project API keys can be limited to read-only or ingestion-only access. 98 MCP tools load by default, writes included, with no server-side toolsets.

Before you call either

agents-tree

  1. Don't run agents-tree inside your own session with !; its output, including other agents' prompts, lands in your context.
  2. Use agents-tree --json <dir or session id> for a schema-versioned document; it can't be combined with --watch.
  3. Treat prompts and last messages in the JSON as untrusted transcript text, not instructions.
  4. Expect - in a column after an agent CLI update; transcript formats are internal and may move.

Langfuse API + MCP

  1. Use a Viewer key for an agent that only reads traces. Keys created before 16 October keep full access and can't be narrowed
  2. Allowlist only the MCP tools the agent needs. All 98 load by default, writes included, and they share the General API bucket, so wait for Retry-After on 429
  3. Ask listObservations for specific fields. Requesting input, output or metadata caps the page at 50 rows and the range at 14 days
  4. Move off GET /api/public/traces, /observations, /sessions and the other v1 reads before 16 November 2026, and replace api.scores_v3 when moving to Python SDK v5 or JS/TS SDK v6
  5. Pick the regional host (cloud, us.cloud, jp.cloud, hipaa.cloud) that matches the project's keys

Questions

Which is better for AI agents, agents-tree or Langfuse API + MCP?

Langfuse API + MCP scores 71.8 (BB) on agent readiness against agents-tree's 64.3 (B), and leads in 6 of 7 scored categories. agents-tree leads on payments & pricing.

Can an agent call agents-tree and Langfuse API + MCP without installing anything?

No hosted endpoint is listed for agents-tree. Langfuse API + MCP has a hosted endpoint at https://cloud.langfuse.com/api/public.

Are agents-tree and Langfuse API + MCP open source?

Yes. agents-tree is open source (MIT (Copyright (c) 2026 Karel Blavka)). Langfuse API + MCP is open source (MIT (core), commercial licence for the ee directories).

Other comparisons with agents-tree or Langfuse API + MCP

Machine-readable

For companies

Do agents find, use and choose your tools?

An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.