flama — security grade SAFE, quality 70/100

Security audit verdict: SAFE · quality 70/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by vortico · MCP Server · ★ 297

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is flama safe to install? View the security audit →

About flama

Light up your models 🔥 Flama The production framework for Predictive and Generative AI. Turn any model into a production API in a single line of code. Serve predictive and generative mode

anthropicasgichatbotdomain-driven-designgenerative-aiinferencellmllm-servingmachine-learningmcp

Quick Facts

Stars297
Forks16
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score69.5484855334041/100
Open Issues10
Last Updated2026-09-14
Created2018-09-27
Platformsbrowser, mcp, python
Est. Tokens~16k

Compatible Skills

These tools work well together with flama for enhanced workflows:

  • any-llm — semantic(0.16)+complementary+shared_fw(anthropic,ollama,openai)+rare_topics+same_lang+similar_pop+shared_platform (80%)
  • mlx-omni-server — semantic(0.23)+complementary+shared_fw(anthropic,openai)+rare_topics+same_lang+similar_pop+shared_platform (79%)
  • llm-rosetta — semantic(0.19)+complementary+shared_fw(anthropic,ollama,openai)+same_lang+similar_pop+shared_platform (77%)
  • clawcode — semantic(0.17)+complementary+shared_fw(anthropic,ollama,openai)+same_lang+similar_pop+shared_platform (76%)
  • flock — semantic(0.20)+complementary+shared_fw(anthropic,ollama,openai)+rare_topics+similar_pop (76%)

flama alternative? Top 6 similar tools

Looking for a flama alternative? If you're comparing flama with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • tools by strands-agents · ⭐ 1.3k

    A set of tools that gives agents powerful capabilities.

  • samples by strands-agents · ⭐ 852

    Agent samples built using the Strands Agents SDK.

  • BambooAI by pgalko · ⭐ 791

    A Python library powered by Language Models (LLMs) for conversational data discovery and analysis.

  • agent-builder by strands-agents · ⭐ 424

    An example agent demonstrating streaming, tool use, and interactivity from your terminal. This agent builder c

  • mcp-server by strands-agents · ⭐ 293

    This MCP server provides documentation about Strands Agents to your GenAI tools, so you can use your favorite

  • tuui by AI-QL · ⭐ 1.2k

    A desktop MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Mode

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Frequently Asked Questions

What is flama?

flama is The production framework for Predictive and Generative AI. Serve any model as an API in one line, with OpenAI/Anthropic/Ollama-compatible endpoints, a built-in chat UI, and native MCP.. It is categorized as a MCP Server with 297 GitHub stars.

What programming language is flama written in?

flama is primarily written in Python. It covers topics such as anthropic, asgi, chatbot.

How do I install or use flama?

You can find installation instructions and usage details in the flama GitHub repository at github.com/vortico/flama. The project has 297 stars and 16 forks, indicating an active community.

What license does flama use?

flama is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to flama?

The top alternatives to flama on Agent Skills Hub include tools, samples, BambooAI. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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