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 RasaHQ/rasa-agent-skills --skill rasa-calling-mcp-tools-from-flowsgit clone --depth 1 https://github.com/RasaHQ/rasa-agent-skillsWrote 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/rasahq/rasa-agent-skills/rasa-calling-mcp-tools-from-flows)<a href="https://agentmods.dev/skills/rasahq/rasa-agent-skills/rasa-calling-mcp-tools-from-flows"><img src="https://agentmods.dev/badge/skills/rasahq/rasa-agent-skills/rasa-calling-mcp-tools-from-flows/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/rasahq/rasa-agent-skills/rasa-calling-mcp-tools-from-flows"><img src="https://agentmods.dev/badge/skills/rasahq/rasa-agent-skills/rasa-calling-mcp-tools-from-flows.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 | $0.00056 | $0.01144 |
| Opus 5.5 | $0.00022 | $0.00458 |
| Sonnet 5.5 | $0.00011 | $0.00229 |
| Haiku 4.5 | $0.00006 | $0.00114 |
Grade A, and why
rasa-calling-mcp-tools-from-flows 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Calling MCP Tools from Flows
MCP tools can be invoked directly from flow steps using a call step with explicit
input/output mappings. This replaces the need for custom action code when you only need
to call an external API.
MCP servers must be defined in endpoints.yml before calling their tools. See the
rasa-configuring-mcp-server skill for server setup and authentication.
This feature is in beta and available starting from Rasa 3.14.0.
When to use MCP vs a custom action
Use an MCP tool call when:
- The tool already exists on an MCP server
- You just need to pass slot values in and store results back
- No complex logic around the call (branching, retries, multiple sequential API calls)
Use a custom action instead when:
- You need complex business logic (multiple API calls, conditionals, error handling)
- You need access to the full tracker (conversation history, events, sender ID)
- You need to send custom messages via the dispatcher
- The data transformation can't be expressed in a Jinja2 output mapping
- The external API isn't exposed via MCP
See rasa-writing-custom-actions for custom action guidance.
Workflow
- Ensure the MCP server is defined in
endpoints.yml(seerasa-configuring-mcp-serverskill). - Call the MCP tool from a flow using a
callstep withmcp_serverandmapping(see "Calling an MCP tool from a flow"). - Map tool results to slots, handling both structured and unstructured output (see "Tool result formats").
- Validate the project.
Calling an MCP tool from a flow
Use a call step with mcp_server and mapping to invoke a tool directly.
| Key | Required | Description |
|---|---|---|
call |
yes | Tool name as exposed by the MCP server |
mcp_server |
yes | Must exactly match a name in endpoints.yml. Fails at runtime if mismatched |
mapping.input |
yes | Maps slot values to tool parameters. Each entry: param (tool parameter name) + slot (Rasa slot name) |
mapping.output |
yes | Maps tool results back to slots. Each entry: slot (target slot) + value (Jinja2 expression to extract the result) |
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.
- 2mo ago First seen · 132 lines · 56 tokens per session scan A 5fb3b4f85cd7
rasa-calling-mcp-tools-from-flows is a skill published in the GitHub repository RasaHQ/rasa-agent-skills (6 stars, last pushed 29d ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,144 once invoked, about $0.0002 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 2026-08-31.
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