Public record
Software health reportschema 0.11.0 · metrics 1.13.0 · 2026-07-17 00:53 UTC

langchain-ai / agent-protocol

PythonMIT★ 634 stars⑂ 55 forkssince Nov 2024View on GitHub ↗

langchain-ai/agent-protocol holds a health index of 58 out of 100, placing it in the Moderate band. It scores highest on AI Readiness (81/100) and lowest on Security (1/100). It was last updated 28 days ago. A single contributor accounts for most of its recent work.

58
overall / 100
Moderate

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.

58
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

Ownership

LangChainOrganization
20,912 followers251 public repossince Mar 2023

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIap_client0.1.19-183 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

70Good · 22% of overall
How it's scored
28.8/36Push recency — last push 28 days ago
6.9/36Commit cadence — 10/52 weeks with commits
13.5/18Commit volume — 31 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year31
human_commit_share
days_since_last_push28
active_weeks_last_year10
How it's scored
27/27Ships releases — 14 releases published
36/36Release recency — latest release 28 days ago
19.8/27Release cadence — a release every ~53 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count14
latest_release_taglangchain-protocol==0.0.18
releases_from_tagsno
days_since_latest_release28
mean_days_between_releases53

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

74Good · 18% of overall
How it's scored
45.4/60Stars — 634 stars
14.4/25Forks — 55 forks
5/15Watchers — 9 watchers
Inputs used
forks55
stars634
watchers9
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
has_contributingyes
has_issue_templateno
has_code_of_conductyes
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

63Moderate · 24% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6.6/22.5Commit distribution — top contributor authored 71% of commits
13.5/13.5Contributor breadth — 13 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled13
top_contributor_share0.707
How it's scored
15.6/46.8Issue resolution — 33% of issues closed
34.4/38.3PR acceptance — 54/60 decided PRs merged
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs54
open_issues12
closed_issues6
issue_closed_ratio0.333
closed_unmerged_prs6
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
25/25Owner reach — 20,912 followers of langchain-ai
19.8/25Track record — 251 public repos, account ~3 yr old
Inputs used
followers20,912
owner_typeOrganization
is_verified
owner_loginlangchain-ai
public_repos251
account_age_days1,233
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 3 days ago
20/20Version history — 18 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesap_client
ecosystemspypi
any_deprecatedno
min_days_since_publish3

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 20% of overall
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

55Moderate
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://langchain-ai.github.io/agent-protocol/api.html
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepagehttps://langchain-ai.github.io/agent-protocol/api.html
has_readmeyes
has_docs_dirno
has_descriptionno

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

1Critical · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfilespnpm-lock.yaml, poetry.lock, uv.lock
manifestsclient-python/pyproject.toml, client-python/requirements.txt, client-python/setup.cfg, client-python/setup.py, server/pyproject.toml, streaming/package.json, tooling/pyproject.toml
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score.

81Good · 0% of overall
How it's scored
45/45Agent instructions — client-python/docs/Agent.md
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
legible_history_share
agent_instruction_filesclient-python/docs/Agent.md
agent_instruction_max_bytes1,025
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
18/18One-command bootstrap — tooling/Makefile
22/22Automated tests
11/11Lint / format config — tox.ini
11/11Static type checking — client-python/ap_client/py.typed, streaming/py/langchain_protocol/py.typed
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfilespnpm-lock.yaml, poetry.lock, uv.lock
has_dockerfileno
typed_languageno
bootstrap_filestooling/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsclient-python/ap_client/py.typed, streaming/py/langchain_protocol/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
27/45Type-checkable code — Python with type-check config (client-python/ap_client/py.typed, streaming/py/langchain_protocol/py.typed)
53.9/55Manageable file sizes — 2/101 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes74,569
source_files_sampled101
oversized_source_files2
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — openapi.json
0/20MCP server
0/40Runnable examples
Inputs used
example_dirs
has_mcp_signalno
api_schema_filesopenapi.json

Key facts

634GitHub stars
13contributors
31commits, last 12 months
28days since last push
14releases
1bus factor
12open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Could not fetch pypi package 'ap-server' from its registry
  • Could not fetch pypi package 'ap-tooling' from its registry
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 12
RegistryPackageVersion constraintManifest
PyPIurllib3>= 2.1.0, < 3.0.0client-python/pyproject.toml
PyPIpython-dateutil>= 2.8.2client-python/pyproject.toml
PyPIpydantic>= 2client-python/pyproject.toml
PyPItyping-extensions>= 4.7.1client-python/pyproject.toml
PyPIpydantic(>=2.10.6,<3.0.0)server/pyproject.toml
PyPIfastapi(>=0.134.0)server/pyproject.toml
npmcddl2py^0.2.2streaming/package.json
npmcddl2ts^0.9.1streaming/package.json
PyPIfastapi-code-generator(>=0.5.2,<0.6.0)tooling/pyproject.toml
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PyPIautoflake(>=2.3.1,<3.0.0)tooling/pyproject.toml
PyPIruff(>=0.9.4,<0.10.0)tooling/pyproject.toml
All dependencies 146

Full resolved dependency set from the GitHub dependency graph: 19 direct and 127 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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Raw JSON report machine-readable
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        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
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        "weight": 0,
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            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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            ],
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              "agent_instruction_max_bytes": 1025
            },
            "components": [
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                "key": "agent_instructions",
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                "points": 45,
                "status": "met",
                "details": [
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                    "code": "file_list",
                    "params": {
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                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
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                "points": 0,
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              },
              {
                "key": "legible_commit_history",
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                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "excellent",
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            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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                }
              },
              {
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              }
            ],
            "value": 100,
            "inputs": {
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              "lockfiles": [
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              "has_dockerfile": false,
              "typed_language": false,
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              "has_devcontainer": false,
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              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
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                "points": 18,
                "status": "met",
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              {
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                "points": 22,
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                "status": "met",
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              },
              {
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                "status": "met",
                "details": [
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                ],
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              },
              {
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                "points": 10,
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              {
                "key": "demonstrated_agent_practice",
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                  }
                ],
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              },
              {
                "key": "automated_maintenance",
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                "status": "excluded",
                "details": [
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                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "OpenSSF Scorecard unavailable",
                "points": 0,
                "status": "excluded",
                "details": [
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                ],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 81,
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              "source_files_sampled": 101,
              "oversized_source_files": 2
            },
            "components": [
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                "status": "partial",
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                    }
                  }
                ],
                "max_points": 45
              },
              {
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                "detail": "2/101 source files over 60KB",
                "points": 53.9,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
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                      "oversized": 2
                    }
                  }
                ],
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              }
            ]
          },
          {
            "key": "ai_interfaces",
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            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
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            },
            "components": [
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                "key": "api_schema_openapi_graphql_proto",
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              },
              {
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              },
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            ]
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        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "Could not fetch pypi package 'ap-server' from its registry",
    "Could not fetch pypi package 'ap-tooling' from its registry",
    "OpenSSF Scorecard timed out after 240s; skipping Scorecard checks"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-17T00:53:45.064613Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/l/langchain-ai/agent-protocol.svg",
  "full_name": "langchain-ai/agent-protocol",
  "license_state": "standard",
  "license_spdx": "MIT"
}

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v1.13.0, schema v0.11.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.