swarms-tools

Swarms Tools is a Python package that provides a collection of pre-built utilities/tools intended for agent use. Based on the README structure and examples, it includes finance/market data tools (e.g., HTX, stock news, Yahoo Finance, CoinGecko, DeFi TVL), social/media integrations (Telegram, Twitter/X, web scraping), and developer tools (GitHub automation, a code executor), plus a tool orchestration helper (tool_chainer) for sequential/parallel execution.

Evaluated Mar 30, 2026 (22d ago)
Homepage ↗ Repo ↗ DevTools python agents tools mcp multi-agent httpx data-integration web-scraping social-media finance
⚙ Agent Friendliness
40
/ 100
Can an agent use this?
🔒 Security
46
/ 100
Is it safe for agents?
⚡ Reliability
25
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
35
Documentation
55
Error Messages
0
Auth Simplicity
55
Rate Limits
10

🔒 Security

TLS Enforcement
70
Auth Strength
40
Scope Granularity
20
Dep. Hygiene
45
Secret Handling
55

Based on the README examples, credentials are expected via environment variables/options (reasonable practice), but the provided content does not confirm TLS/HTTPS enforcement, secure secret logging behavior, fine-grained authorization scopes, or robust error handling that avoids leaking secrets. The package depends on several broad libraries (e.g., httpx, mcp, lxml, backoff, orjson); dependency health/CVEs are not verifiable from the provided data.

⚡ Reliability

Uptime/SLA
0
Version Stability
45
Breaking Changes
35
Error Recovery
20
AF Security Reliability

Best When

You want ready-made Python functions/classes to call external services from within an agent and you can supply required credentials for the specific integrations you enable.

Avoid When

You cannot audit the underlying tool implementations (especially for web scraping and any code-execution capability) or you require strong, documented operational guarantees (rate limits, retry behavior, idempotency, structured error codes).

Use Cases

  • Augmenting LLM/agent workflows with external data (market data, news, crypto/DeFi metrics)
  • Automating social and messaging tasks (e.g., Telegram DM/tag, Twitter/X posting via a plugin interface)
  • Scraping web content for downstream analysis
  • Agent-assisted developer workflows (GitHub repository operations, lightweight code execution for automation)
  • Orchestrating multiple tools in parallel or sequence within a multi-agent workflow

Not For

  • Production-grade security-sensitive automation without reviewing tool implementations and dependency supply chain
  • Use cases requiring a documented, first-class public REST/GraphQL API contract
  • Environments that require explicit rate-limit and retry/idempotency guarantees from the library itself

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
Yes
Webhooks
No

Authentication

Methods: API keys / secret values via options or environment variables (implied by examples such as TWITTER_* credentials) Potentially provider-specific tokens for each integrated service (not fully specified in README)
OAuth: No Scopes: No

The README shows credentials passed through an options dict and loaded from env vars for TwitterTool. There is no evidence in the provided content of OAuth flows or fine-grained scopes being managed by the library itself.

Pricing

Free tier: No
Requires CC: No

README indicates installation via pip; no pricing details are provided for the package itself.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • The package integrates many third-party services; failures may propagate from upstream APIs, requiring agent-side retry/backoff handling.
  • A 'code executor' and social posting tools increase operational risk; ensure you understand safety controls and sandboxing before agent use.
  • Web scraping may be sensitive to robots.txt, rate limits, and HTML structure changes; agent workflows should handle extraction failures gracefully.

Alternatives

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Scores are editorial opinions as of 2026-03-30.

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