Google Flights MCP (fli)

Google Flights MCP, CLI and Python Library

MCP Servers Python Grade B Listed MIT
69.6/100
Rank #145 of 1283
Compare Google Flights MCP (fli)

Promising trust profile, but some evidence still deserves review.

Open compare tool Suggest correction
Listing state
Listed
Evidence coverage
Grade B · 3/5 signals
Last push
2026-07-20 · 23d ago
Recent change
New

Is Google Flights MCP (fli) safe? Google Flights MCP (fli) scores 69.6/100 (Grade B), ranked #145 of 1283 tracked open-source AI agent projects, on evidence coverage B (3 of 5 independent signal types). The public evidence: its packages ship with cryptographic provenance; no OSSF Scorecard result yet; 94% of recent commits are signed; last pushed 2026-07-20. Every point is earned from checkable signals — never paid placement. How scoring works →

Ranked neighbours in MCP Servers

Quick Trust Read

What Would Improve It
Add or improve OSSF Scorecard coverage so safety checks are easier to verify.
Recent Changes
2026-08-10
Newly Listed
First tracked at rank #144
Maintainer Checklist
Add Scorecard coverage Expose the repository to OpenSSF Scorecard checks so supply-chain posture is easier to verify.
54.8
Activity sub-score · out of 100
#32

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade B reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage B is separate — it grades how many independent signal types back the score (3 of 5), so a high score on thin evidence stays visible. Full methodology →

Signals refreshed 2026-08-12 05:02 UTC · Repo last pushed 23 days ago

Rank Trend

2026-08-11 2026-08-12

Activity & Reach

Stars
3.1k
Forks
380
Last Push
2026-07-20
23 days ago
Commits (4 wk)
0
Downloads (7d)
51,352
pypi
HN mentions (30d)
Open Issues
22
Rank Change
=
was #145

Analysis

HVTrust Dimensions vs MCP Servers

69.6 / 100 · 100.0% confidence

Google Flights MCP (fli) MCP Servers average (761 agents)

Safety / Integrity50% OSSF Scorecard · 30% provenance · 20% signed commits
12.2 / 25
7.2 above avg 5.0
Identity / Provenance60% listing status · 40% build provenance
18.0 / 18
4.7 above avg 13.3
Transparency50% declared license · 50% OSSF Scorecard
8.5 / 17
in line with avg 8.8
Maintenance60% last-push freshness · 40% commit activity
10.5 / 20
1.9 below avg 12.4
AdoptionLog-scaled stars · package downloads
14.7 / 20
8.9 above avg 5.8

Activity Inputs

54.8 / 100
StarsRepository reach
20.9 / 30
FreshnessLast push recency
21.8 / 25
ActivityRecent commits
0.0 / 25
CommunityFork signal
12.0 / 20

Supply Chain Trust

Package Provenance
Verified
pypi attestation
OSSF Scorecard
Not available
Signed Commits
94%
of last 100 commits verified

Is Google Flights MCP (fli) safe?

Google Flights MCP (fli) has a mixed signal profile. Some trust indicators are present, others are missing. Whether it is safe for your use case depends on which gaps matter to you — review the breakdown below before adopting in production.
Does Google Flights MCP (fli) publish package provenance?
Yes. Google Flights MCP (fli)'s package releases carry build provenance attestations, which cryptographically link the published package back to its source repository and CI workflow.
Does Google Flights MCP (fli) have an OpenSSF Scorecard?
No OpenSSF Scorecard data is currently published for Google Flights MCP (fli). Maintainers can enable the Scorecard GitHub Action to get a public score; without it, automated supply-chain hygiene is harder for outsiders to verify.
Is Google Flights MCP (fli) actively maintained?
Maintained. Last push was 23 days ago.
What license does Google Flights MCP (fli) use?
Google Flights MCP (fli) ships under MIT. A declared, OSI-approved license is one of the transparency signals HVTrust scores.
Are Google Flights MCP (fli)'s commits signed?
94% of the last 100 commits to Google Flights MCP (fli) are verified-signed (GPG, SSH, S/MIME, or GitHub's signing flow). Signed commits help confirm that code was authored by who the commit claims.

Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.

AI agent surface

MCP, providers, tool surface
Scored in HVTrust

These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →

MCP Server Support
high confidence
Implemented
Google Flights MCP (fli) appears to expose MCP server capabilities.
Detailed evidence is not shown in the public view.
External Service Dependencies
None detected
No clear third-party provider dependency detected.
Credential signal: No explicit API-key/config marker detected.
Tool / Plugin Surface
medium confidence
Declared
Declared plugin/integration surface detected.
Detailed evidence is not shown in the public view.
Package Provenance Drift
high confidence
Match
Published package metadata matches the tracked repo
Detailed evidence is not shown in the public view.
  • MCP signal live
  • External deps live
  • Tool / plugin surface live
  • Package provenance drift live

Maintain Google Flights MCP (fli)?

For maintainers

HVTrust scores Google Flights MCP (fli) from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.

Reputation Timeline

Signal history
Listed 1
2026-08-10
Newly Listed
First tracked at rank #144

Embed Badge Badge guide for maintainers →

For maintainers
HVTrust 69.6 Grade B
Markdown:
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HTML:
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Other agents in MCP Servers

Data sources
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance)
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.3 · Raw JSON