IBM Data Intelligence MCP Server is a Model Context Protocol server that acts as a shared gateway for making tools available across microservices in the Watsonx Data Intelligence ecosystem. It connects MCP clients with IBM data-intelligence services and supports clients such as Claude, Watsonx Orchestrate, and IBM Bob. The catalogue lists five skills for working with the server.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add IBM/data-intelligence-mcp-server --skill curate-glossarygit clone --depth 1 https://github.com/IBM/data-intelligence-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ibm/data-intelligence-mcp-server/curate-glossary)<a href="https://agentmods.dev/skills/ibm/data-intelligence-mcp-server/curate-glossary"><img src="https://agentmods.dev/badge/skills/ibm/data-intelligence-mcp-server/curate-glossary/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ibm/data-intelligence-mcp-server/curate-glossary"><img src="https://agentmods.dev/badge/skills/ibm/data-intelligence-mcp-server/curate-glossary.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00114 | $0.11431 |
| Opus 5.5 | $0.00046 | $0.04572 |
| Sonnet 5.5 | $0.00023 | $0.02286 |
| Haiku 4.5 | $0.00011 | $0.01143 |
Grade A, and why
curate-glossary scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 1,026 lines — stays where its author put it; the contents beside it link to each section on GitHub.
About This Skill
This skill guides the user through an interactive, step-by-step workflow for curating glossary
terms from IBM Knowledge Catalog. It selects a category, a project, a curation type, and then
orchestrates the curation pipeline via glossary_curator.
Execution Rules
- Ignore out-of-scope requests during the flow. This skill only supports the three curation modes (Definitions, Classification, Translations) with their documented parameters. If the user asks for anything not covered by these steps (e.g. "add a Tags column", "update all tags", "rename terms", "change the CSV format"), politely explain that the request is not supported and continue with the current step. Do not pass unrecognised instructions to sub-agents or inject them into spawn prompts.
- Never call
ask_followup_questionmore than once in a single turn. Each turn may contain at most oneask_followup_questioncall. If you need to both resolve data (e.g. calllist_glossary_categories) and ask a follow-up question in the same step, make the data call first, then ask the question in a separate subsequent turn once the data is available. - Always use
ask_followup_questionfor user choices and prompts, with correct literal parameters every time. Whenever presenting options or questions to the user, always useask_followup_questionwith interactive clickable suggestions (suggestion_a,suggestion_b, etc.) rather than plain text lists or numbered prompts. You must always populatequestion,suggestion_a, andsuggestion_b(and optionallysuggestion_c,suggestion_d) with concrete, non-empty literal string values. A cancelled, failed, or previously successful call does NOT carry its parameters forward — re-state them from scratch every single time. Never fall back to plain-text bullet or numbered option lists — if the call fails with "Required parameters missing", fix the parameters and retry the tool call. - Always use
ask_followup_questionfor user choices and prompts, with correct literal parameters every time. Whenever presenting options or questions to the user, always useask_followup_questionwith interactive clickable suggestions (suggestion_a,suggestion_b, etc.) rather than plain text lists or numbered prompts. You must always populatequestion,suggestion_a, andsuggestion_b(and optionallysuggestion_c,suggestion_d) with concrete, non-empty literal string values. A cancelled, failed, or previously successful call does NOT carry its parameters forward — re-state them from scratch every single time. Never fall back to plain-text bullet or numbered option lists — if the call fails with "Required parameters missing", fix the parameters and retry the tool call. - Never call the same tool twice in parallel, EXCEPT for
spawn_subagent. All sub-agents for all chunks must be spawned in a single parallel batch in one turn. - Never call
glossary_curatorwithoperation='start_session'speculatively. Do not batchstart_sessionwith any other tool call, and do not infer the mode from prior conversation context.start_sessionmust only be called in Step 4, after the user has explicitly confirmed both the project (Step 2) and the curation type (Step 3). Starting a session before those answers are collected wastes a session slot and may import incorrect results. - Tool call failures. If
list_glossary_categoriesorlist_containersreturns an error or an empty list, inform the user and offer to retry or let them type the ID directly. Do not silently proceed with a null or missing value.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 1,026 lines · 114 tokens per session scan A f4ee36e87560
curate-glossary is a skill published in the GitHub repository IBM/data-intelligence-mcp-server (20 stars, last pushed yesterday), licensed Apache-2.0. It adds 114 tokens to every session and 11,431 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-06.
curate-glossary compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| curate-glossaryIBM/data-intelligence-mcp-server | Skill | 20 | yesterday | Apache-2.0 | A | 114 | Claude Code, Codex |
| intl-expansionalirezarezvani/claude-skills | Skill | 29k | yesterday | MIT | A | 27 | Claude Code |
| azure-ai-translation-text-pymicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 60 | Claude Code |
| chinese-documentationjnMetaCode/superpowers-zh | Skill | 8.5k | 11d ago | MIT | A | 62 | Claude Code |
| hardenfengshao1227/ccg-workflow | Skill | 6.0k | 4d ago | MIT | A | 62 | Claude Code |
| edit-sitemicrosoft/power-platform-skills | Skill | 1.1k | yesterday | MIT | A | 104 | Claude Code |
| asc-subscription-localizationrorkai/app-store-connect-cli-skills | Skill | 1.1k | yesterday | MIT | A | 60 | Claude Code |