io.github.JcJamet/ia-qa-toolbox

up checked 2026-11-11T04:39:07.851Z

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Publisher-provided title

IA-QA — 152 QA & Dev Tools for AI Agents

Publisher-provided description

152 free QA tools for agents: injection scan, evals, RAG, web audits. Smaller packs: /mcp/{pack}.

Summary by lookupd

Runs QA checks for AI agents: prompt injection and secret scans, evals, RAG and hallucination tests, diff linting, and CI workflow…

Install

Claude Code, remote (streamable-http)

claude mcp add --transport http ia-qa-toolbox https://www.ia-qa.com/mcp

Codex, remote (streamable-http)

codex mcp add ia-qa-toolbox --url https://www.ia-qa.com/mcp

Cursor, remote (streamable-http) → .cursor/mcp.json

{
  "mcpServers": {
    "ia-qa-toolbox": {
      "url": "https://www.ia-qa.com/mcp"
    }
  }
}

Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.

Tools (showing 30 of 153)

Publisher-provided text

• get_testing_guidelines Query the IA-QA methodology knowledge base. Returns structured testing guidelines, assertion strategies, thresholds, best practices, and relevant MCP tools for
• find_tool Search available MCP tools by keyword or category before calling them. Returns names, descriptions and, on request, inputSchemas. Queries are logged 90 days, sc
• generate_test_cases Generate a set of test cases (valid, edge, invalid, pairwise) for a given feature description. Declared constraints drive the boundaries: a length or numeric bo
• jira_to_test_suite Turn a Jira ticket into a test suite: Gherkin scenarios, E2E steps, API tests, test data and the ambiguities to clarify. Pass the issue object, or Jira credenti
• analyze_diff_bugs Pattern-based diff linter: flags a fixed set of risky shapes in changed code — query-string interpolation (SQL/Cypher/Mongo injection shape), shell interpolatio
• run_pr_gate_pipeline Review triage for a pull request. Takes a unified git diff (`git diff HEAD`) and returns: diff-lint findings with the lines that produced them, regression impac
• diff_mappings Diff a baseline page mapping against a current one and return a CI-style verdict: PASS / FIX / BLOCK, plus per-element drift (ok, renamed, healable, ambiguous,
• sandbox_scenario Get a ready-made selector-drift test case with a known-correct answer, for testing this MCP server or an agent workflow end to end. Each scenario is a real DOM
• prompt_injection_scan Scan user input or prompts for prompt injection patterns. Pattern-based: it recognises known phrasings and structures, not intent — an uncovered paraphrase or l
• hallucination_check Lexical hallucination check: verifies an LLM answer's words, numbers and polarity against the provided source/context. Fast, deterministic, no API key needed. E
• run_eval_contract Run an IA-EVAL test suite (.ia-eval.yaml contract): call the model per scenario; return passed (true, false, null if undecided) and a verdict (PASS, FAIL, PARTI
• guardrail_test Test an LLM response against a set of guardrail rules: must-include, must-not-include, max length, required format, language, forbidden patterns, and custom reg
• run_semantic_tests Semantic assertion primitive: compare actual vs expected text pairs using cosine similarity + ROUGE-L. Two modes: tfidf (default, free, no API key) or embedding
• generate_ci_workflow Generate a ready-to-commit GitHub Actions workflow that gates a build on IA-QA: "eval_contract" runs a .ia-eval.yaml through ia-qa-com/eval-action@v1 (needs a p
• redact_pii Automatically detect and redact Personally Identifiable Information (PII) from text. Replaces emails, phone numbers, SSNs, IBANs, credit cards, IP addresses, an
• secret_scan Scan text or code for leaked secrets: API keys (AWS, GCP, Azure, OpenAI, Anthropic, Stripe, GitHub, GitLab, Slack, Twilio, SendGrid, HuggingFace), Slack / Teams
• needle_haystack_generate Generate a "needle in a haystack" test: embeds a target fact into a large block of filler text at a specified position. Use this to test LLM context window retr
• list_local_tests Discover .ia-eval.yaml LLM test suite files in the project directory. Scans CWD and standard sub-directories (evals/, tests/, contracts/). Returns file paths re
• generate_html_report Convert a run_eval_contract() LLM Test Runner JSON result into a fully self-contained dark-themed HTML report with Pass/Fail badges, side-by-side Input/Output/G
• generate_eval_yaml Generate a complete .ia-eval.yaml evaluation contract from a plain-language description of what your LLM should do. Uses Groq openai/gpt-oss-20b (server-side, n
• validate_agent_trajectory Run declarative assertions on an agent trace (OpenAI tool calls, Anthropic tool_use, LangChain run trees, ReAct logs). Deterministic, no LLM. Assertions: order
• metamorphic_check Reference-free stability check: does an assistant's answer stay the same when the QUESTION is transformed (case, typo, paraphrase, reorder, translation)? You br
• test_skill Test a SKILL.md. No model, every call: lint (gate on lint.valid) and review (description lacks what/when, words shared with other_skills, leftovers, no done-che
• skill_interview Help a person write a SKILL.md they can test. No answers: the questions (why + example), written for the person; invented answers make the result meaningless. W
• diff_text Compute a unified line-by-line diff between two text strings (LCS algorithm). Returns added/removed/unchanged line counts and formatted diff hunks with configur
• validate_mcp_response Validate that an MCP tool response conforms to expected format, schema, and content rules. Use this to QA-test any MCP server tool. Supply the tool's actual JSO
• llm_output_validator Validate an LLM response against QA criteria: format checks (JSON, code, markdown), content rules (must-include, must-not-include), length constraints, language
• compare_responses Compare two ALREADY-PRODUCED outputs (e.g. model A vs model B on the same task) side by side. Returns deterministic metrics (token cosine, ROUGE-L, Jaccard, len
• analyze_responses Semantically analyze N already-produced model outputs for the SAME task (the MCP counterpart to the LLM Sandbox). Without a reference: computes consensus — pair
• prompt_test_suite Define a test suite for a prompt: provide the system prompt, user prompt, and expected output criteria. Returns a test plan with scored rubric — use this as inp

Details

• Version: 1.1.1
• Transports: streamable-http
• Uptime (7 days): 100%
• Median latency: 848 ms
• First indexed: 2026-11-01T09:10:57.671Z
• Last seen in registry: 2026-11-01T09:10:57.691Z
• Repository: https://github.com/ia-qa-com/mcp

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