Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-13 10:40 UTC

jonigl / mcp-client-for-ollama

Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.

PythonMIT★ 819 stars⑂ 124 forkssince Apr 2025View on GitHub ↗
KindCommand-line toolMCP serverLibraryhow this is determined

jonigl/mcp-client-for-ollama holds a health index of 80 out of 100, placing it in the Excellent band. It scores highest on Vitality (92/100) and lowest on AI Readiness (47/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.

80
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

80
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe 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.

The weighted overall 68 is calibrated to 80 on the published index scale (record calibration 2026-08-02).

Ownership

74 followers66 public repossince Jun 2013

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPImcp-client-for-ollama0.35.04,807661 day ago
PyPIollmcp0.35.04,225631 day ago

Metrics by category

Vitality

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

92Excellent · 21% of overall
How it's scored
36/36Push recency — last push 1 days ago
22.8/36Commit cadence — 33/52 weeks with commits
18/18Commit volume — 132 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year132
human_commit_share0.88
days_since_last_push1
active_weeks_last_year33

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 60 releases published
36/36Release recency — latest release 1 days ago
27/27Release cadence — a release every ~9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count60
latest_release_tagv0.35.0
releases_from_tagsno
days_since_latest_release1
mean_days_between_releases9
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

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

62Moderate · 17% of overall
How it's scored
47.2/60Stars — 819 stars
17.4/25Forks — 124 forks
4.3/15Watchers — 7 watchers
Inputs used
forks124
stars819
watchers7
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno
How it's scored
52.7/80Monthly downloads — 9,032 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmcp-client-for-ollama, ollmcp
dependents—
ecosystemspypi
total_downloads—
monthly_downloads9,032
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

55Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.7/22.5Commit distribution — top contributor authored 97% of commits
9.5/13.5Contributor breadth — 7 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled7
top_contributor_share0.967
How it's scored
33.1/42Issue resolution — 79% of issues closed
22.5/30PR acceptance — 191/255 decided PRs merged
0/13Newcomer PR acceptance — 0/3 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — Found 1/28 approved changesets -- score normalized to 0
Inputs used
merged_prs191
open_issues11
closed_issues41
prs_merged_7d9
prs_decided_7d12
prs_merged_30d17
prs_decided_30d20
issue_closed_ratio0.788
closed_unmerged_prs64
first_time_authors_30d3
first_time_prs_merged_30d0
first_time_prs_decided_30d3
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
13.5/25Owner reach — 74 followers of jonigl
25/25Track record — 66 public repos, account ~13 yr old
Inputs used
followers74
owner_typeUser
is_verified—
owner_loginjonigl
public_repos66
account_age_days4,848
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 2 package(s) on pypi
35/35Publish recency — latest publish 1 days ago
20/20Version history — 66 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmcp-client-for-ollama, ollmcp
ecosystemspypi
any_deprecatedno
min_days_since_publish1

Engineering Quality

Are baseline engineering and documentation practices in place?

65Good · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 29 out of 29 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 20 topics
10/10Wiki
Inputs used
topicsai, command-line-tool, mcp, mcp-client, mcp-server, open-source, model-context-protocol, ollama, local-llm, sse, stdio, streamable-http, linux, macos, windows, agentic-ai, mcp-prompts, mcp-tools, harness, mcp-resources
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

70Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 29 out of 29 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 1/28 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
4.5/5SAST — SAST tool is not run on all commits -- score normalized to 9
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.3
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages49
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:mcp-client-for-ollama@0.35.0 runtime dependency closure — what installing the published package pulls in — 49 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

47Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.databricks.com/llms.txt)
40/40Legible commit history — 88 of 88 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.databricks.com/llms.txt
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
4/10Demonstrated agent practice — 2 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 12 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0.02
toolchain_manifests—
dependency_bot_commit_share0.12
How it's scored
0/45Type-checkable code — Python without a type-check config
54.3/55Manageable file sizes — 1/78 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes112,514
source_files_sampled78
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalyes
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

819GitHub stars
7contributors
132commits, last 12 months
1days since last push
60releases
1bus factor
11open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 124 ⇿
0Stars
124Forks
53Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

025507510012512232025-042026-012026-09
Major 0Minor 31Patch 22

Each point covers 2 days.

OpenSSF Scorecard 6.3 / 10
6.3aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-13 10:40 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests29 out of 29 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/28 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
9SASTSAST tool is not run on all commits -- score normalized to 9
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 7
RegistryPackageVersion constraintManifest
PyPImcp-client-for-ollama==0.35.0cli-package/pyproject.toml
PyPIany-llm-sdk~=1.27.2pyproject.toml
PyPIhttpx>=0.27,<1pyproject.toml
PyPImcp~=2.1.1pyproject.toml
PyPIprompt-toolkit~=3.0.53pyproject.toml
PyPIrich>=14.2.0,<14.3pyproject.toml
PyPItyper~=0.27.0pyproject.toml
All dependencies 60

Full resolved dependency set from the GitHub dependency graph: 8 direct and 52 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIany-llm-sdk1.27.2direct
PyPIhttpx0.28.1direct
PyPImcp2.1.1direct
PyPImcp-client-for-ollama0.29.1direct
PyPImcp-client-for-ollama0.35.0direct
PyPIprompt-toolkit3.0.53direct
PyPIrich14.2.0direct
PyPItyper0.27.2direct
PyPIannotated-doc0.0.5indirect
PyPIannotated-types0.8.0indirect
PyPIanthropic0.120.2indirect
PyPIanyio4.14.2indirect
PyPIattrs26.1.0indirect
PyPIcertifi2026.7.22indirect
PyPIcffi2.1.1indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcryptography50.0.0indirect
PyPIdistro1.9.0indirect
PyPIdocstring-parser0.18.0indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpcore22.12.0indirect
PyPIhttpx22.12.0indirect
PyPIhttpx2-jsfetch1.0indirect
PyPIidna3.18indirect
PyPIiniconfig2.3.0indirect
PyPIjiter0.16.0indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPImarkdown-it-py4.2.0indirect
PyPImcp-types2.1.1indirect
PyPImdurl0.1.2indirect
PyPIollama0.6.2indirect
PyPIopenai2.53.0indirect
PyPIopenresponses-types2.4.0indirect
PyPIopentelemetry-api1.44.0indirect
PyPIpackaging26.3indirect
PyPIpluggy1.6.0indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.20.0indirect
PyPIpyjwt2.13.0indirect
PyPIpytest9.1.1indirect
PyPIpython-multipart0.0.32indirect
PyPIpywin32312indirect
PyPIreferencing0.37.0indirect
PyPIrpds-py2026.6.3indirect
PyPIsetuptools—indirect
PyPIshellingham1.5.4indirect
PyPIsniffio1.3.1indirect
PyPIsse-starlette3.4.8indirect
PyPIstarlette1.4.1indirect
PyPItqdm4.70.0indirect
PyPItruststore0.10.4indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.2indirect
PyPIuvicorn0.52.1indirect
PyPIwcwidth0.8.2indirect
Dependency advisories 0

Installing pypi:mcp-client-for-ollama@0.35.0 pulls in 49 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

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 v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.