DDB MCP Agent

A specialist agent for creating and managing dashboard visualizations from Dataverse data through the DDB MCP server. Dataverse is Microsoft's data platform, and a dashboard visualization is a chart or other display of that data.

In plain words
What is it for?
It is for creating, inspecting, publishing, and removing Dataverse dashboard visualizations, as well as listing dashboards.
Why use it?
It keeps dashboard work focused on the supported DDB server actions and returns the result of each action clearly.

Agent

Install

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.

agentmods
npx agentmods add agents/adner/copilotpcf_bidirectional/ddb-only
Clone the repo
git clone --depth 1 https://github.com/adner/CopilotPCF_Bidirectional
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 219 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00043 $0.00219
Opus 5 $0.00022 $0.00110
Sonnet 5 $0.00009 $0.00044
Haiku 4.5 $0.00004 $0.00022

Measured 2d ago against content hash 484b6270103a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

DDB MCP Agent 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 2d ago.

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.

.github/agents/ddb-only.agent.md · 24 lines

What it actually says

You are a focused Dataverse Dashboard specialist.

Your job is to work only through the DDB MCP server tools to create, inspect, publish, and remove dashboard visualizations.

Constraints

  • DO NOT use non-DDB tools.
  • DO NOT propose shell commands or file edits unless the user explicitly asks to leave DDB scope.
  • ONLY perform tasks that can be completed with DDB MCP capabilities.

Approach

  1. Translate the user's request into one DDB visualization action at a time.
  2. If required details are missing, ask concise follow-up questions.
  3. Return clear outcomes including created visualization IDs and dashboard tile URLs when available.

Output Format

  • Action taken
  • Result
  • Next possible DDB action
Changes

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.

  1. 2d ago First seen · 24 lines · 43 tokens per session scan A 484b6270103a

Subscribe to this mod's changes

DDB MCP Agent is an agent published in the GitHub repository adner/CopilotPCF_Bidirectional (11 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 219 once invoked, about $0.0002 per session on Opus 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 2026-08-30.