Tidewave MCP runtime tools — debugging, smoke testing, live state inspection, SQL queries, hex docs. Use when evaluating code in a running Phoenix app.
npx skills add https://github.com/oliver-kriska/claude-elixir-phoenix --skill tidewave-integration
Runtime intelligence for Phoenix apps via MCP. Prefer Tidewave tools over Bash when available.
mcp__tidewave__get_docs > web_fetch, execute_sql_query > psql/mcp command or detect mcp__tidewave__ toolsexecute_sql_query for SELECT, be careful with mutationsget_docs returns docs for YOUR mix.lock versions, not latest| Task | Tidewave Tool | Fallback |
|------|---------------|----------|
| Get docs | mcp__tidewave__get_docs Module.func/3 | web_fetch hexdocs.pm/... |
| Run code | mcp__tidewave__project_eval | mix run -e "code" |
| SQL query | mcp__tidewave__execute_sql_query | psql $DATABASE_URL |
| Find source | mcp__tidewave__get_source_location | grep -rn "defmodule" |
| Inspect DOM | mcp__Tidewave-Web__browser_eval | Manual browser inspection |
| List schemas | mcp__tidewave__get_ecto_schemas | Read lib/*/schemas/ |
| Read logs | mcp__tidewave__get_logs level: :error | tail -f log/dev.log |
# Check endpoint
curl -s http://localhost:4000/tidewave/mcp \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"ping"}'
Or use /mcp in Claude Code to see connected servers.
# mcp__tidewave__project_eval
MyApp.Accounts.create_user(%{email: "[email protected]"})
-- mcp__tidewave__execute_sql_query
SELECT column_name, data_type FROM information_schema.columns
WHERE table_name = 'users';
# mcp__tidewave__project_eval
pid = pid("0.1234.0")
:sys.get_state(pid) |> Map.get(:socket) |> Map.get(:assigns) |> Map.keys()
# mix.exs
{:tidewave, "~> 0.6", only: :dev}
# endpoint.ex (in dev block)
plug Tidewave
# config/dev.exs (for LiveView source mapping)
config :phoenix_live_view,
debug_heex_annotations: true,
debug_attributes: true
The dependency and endpoint plug expose Tidewave's streamable HTTP server; they
do not register it with an MCP client. Configure the current runtime separately
with http://localhost:<port>/tidewave/mcp, then verify that Tidewave tools are
available before relying on this skill.
Worktree/port check (FIRST, in multi-worktree setups): multiple
worktrees = multiple dev servers on different ports. Before trusting any
Tidewave result, confirm the endpoint belongs to THIS checkout: grep
config/dev.exs for the configured port, and verify with
project_eval File.cwd!() — if it returns a different worktree path,
you're debugging the wrong server.
Schema introspection BEFORE SQL: never guess column names. Run
get_ecto_schemas (or query information_schema.columns) before writing
SQL against a table you haven't already introspected this session. A
guessed-column error costs more than the introspection.
Output-size guard: runtime output is unbounded. Always cap it —
LIMIT 20 in SQL, Enum.take(20) in evals, `inspect(x, limit: 50,
printable_limit: 500)` for large structs. Re-query narrower rather than
dumping wide.
browser_eval fallback: if mcp__Tidewave-Web__browser_eval is absent
or errors, don't stall — inspect the same state server-side: LiveView
assigns via :sys.get_state(pid) in project_eval, rendered HTML via
Phoenix.LiveViewTest, or read the template source directly.
QA walkthrough pattern: after a feature completes, run a short
checklist through project_eval/browser_eval: create the record, fetch
it back, exercise the main event, check get_logs level: :error is clean.
Report each step's pass/fail — not just "smoke test passed".
Don't just use Tidewave reactively. **Query runtime state at
workflow checkpoints** automatically:
get_logs level: :error (catch runtime crashes)project_eval smoke test (behavioral check)get_ecto_schemas + routes eval (concrete context)browser_eval to inspect DOM state before editing componentsSee ${CLAUDE_SKILL_DIR}/references/proactive-patterns.md for full integration points.
For detailed patterns, see:
${CLAUDE_SKILL_DIR}/references/proactive-patterns.md - Push-like runtime patterns at workflow checkpoints${CLAUDE_SKILL_DIR}/references/tool-examples.md - Complete tool usage examples${CLAUDE_SKILL_DIR}/references/validation-checklist.md - Runtime validation patternsToolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use when implementing any feature or bugfix, before writing implementation code
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Take oliver-kriska/tidewave-integration from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.