Tough Tongue AI Skills
MCP serverDatabases & dataThis app lets your AI create voice-agent scenarios, place SIP calls, pull session analytics, and schedule meeting bots. After adding it, you can ask your AI to handle these voice and meeting tasks for you in plain language.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding the app, ask your AI to create a voice-agent scenario or place a SIP call to try it out. You can also request session analytics or a scheduled meeting bot whenever you need them.
Then ask your AI: use Tough Tongue AI Skills
What your AI can do with it
- Create voice-agent scenarios
- Place SIP calls
- Pull session analytics
- Schedule meeting bots
From the project's README
As published by tough-tongue/toughtongue-skills in README.md.
Agent skills and MCP server for Tough Tongue AI, the platform for handling tough conversations. Some, the AI takes: voice agents that answer and place calls, qualify leads, run demos, screen candidates, and book meetings. Others, you nail: hyper-realistic roleplay that gets you ready for negotiations, interviews, and coaching conversations.
Install once, then work with Tough Tongue AI from Claude Code, Codex, Cursor, or any agent that supports the Agent Skills format:
- "Pull the last 3 lost deals from our call notes and create a practice scenario for the pricing objection."
- "For the Enterprise Discovery Call scenario, pull the last 50 sessions. What are the top 5 improvement areas?"
- "The onboarding agent keeps ending calls too early. Pull the low-scoring sessions, find out why, and fix the scenario."
These compose with the rest of your MCP ecosystem: Gong, Notion, calendar, slides, email. See What you can do for the full journeys.
Table of contents
- What's included
- How this repo is structured
- Prerequisites
- Which setup fits you?
- Set up
- One command, every agent
- Claude Code
- Codex
- Cursor
- Copilot / Windsurf / Gemini CLI / other agents
- Skills only
- MCP only
- Pin a version
- Verify your setup
- What you can do
- MCP Server
- Troubleshooting
- Repository structure
- Related
- License
What's included
This repo ships two layers that work together, plus plugins that bundle both:
Skills — workflow guidance your agent loads automatically when the conversation matches:
| Skill | When it activates | What it does |
|---|---|---|
| ttai-agent | Any Tough Tongue AI / ttai question | Intelligence layer: scope, capability, entities, scenario quality, runtime, MCP guidance |
| scenario-maker | "Create a scenario", "create a voice agent", "fix the scenario", … | Create, edit, or refine scenarios via MCP. |
| session-analyst | "How is my team doing?", "top improvement areas", … | Turn session data into structured reports. |
| browser-demo-builder | "Record browser demo steps", … | Pre-recorded browser demo steps via MCP. |
MCP server — live actions in your Tough Tongue AI account. 27 tools over the public API: scenarios, sessions, analytics, organizations, SIP, meeting bots, and collections. Full catalog in MCP.md.
Plugins (Claude Code, Codex, Cursor) — bundle the skills and the MCP server registration in one install.
How the layers relate:
- ttai-agent is the provider-neutral intelligence layer: it turns intent into scoped, capability-aware decisions using the entity handbook and features/mcp adapter guidance.
- Workflow skills add judgment for a job (create, refine, analyze, record a demo).
- With skills only, your agent can advise. With MCP only, it can call tools. With both, it picks the right workflow and completes it. The plugin gives you both in one step.
Need a specific git tag, commit, or a single skill? See INSTALL.md.
How this repo is structured
flowchart TB
subgraph install["You install one of these"]
P["Plugin — skills + MCP registration"]
Sonly["Skills only — guidance, no live tools"]
Monly["MCP only — 27 ttai tools, no workflows"]
end
subgraph layers["Skill layers — load down, don't copy up"]
L1["Workflows — scenario-maker · session-analyst · browser-demo-builder"]
L0["ttai-agent — kb (entities, recipes) + features/mcp"]
L1 --> L0
end
P --> layers
P --> MCP["Hosted MCP https://api.toughtongueai.com/api/public/mcp"]
Sonly --> layers
Monly --> MCP
Workflow skills tell the agent when. They load ttai-agent for what
exists and how to act. Situation recipes (cold call, sales roleplay,
coaching, demo, cascade TTS) live under
skills/ttai-agent/kb/scenario-recipes/ — not copied into every workflow skill.
The intelligence layer has no terminal or UI dependency. Coding agents load it before calling MCP; web conversational plugins can pass verified account, workspace, and focused-resource context to the same layer, then execute the result through their server-side adapter.
Prerequisites
Every path needs a Tough Tongue AI account — sign up at app.toughtongueai.com.
That's it for interactive setups. Authentication is OAuth-first: the first time your agent calls a Tough Tongue AI tool, the client opens a browser consent page — approve once and the client stores the token (Claude Code and Codex use your system keychain). No environment variables, no app restarts.
Upgrading from a PAT-based install? After updating the plugin you'll see a one-time OAuth prompt (Claude Code: run
/mcpand authenticate; Codex:codex mcp login ttaior approve the automatic prompt). Your existing PAT keeps working for manual/headless configs.
Browser OAuth can't run in headless environments. Create a Personal Access Token (PAT) at app.toughtongueai.com/developer and export it where your agent runs:
export TTAI_PAT="<your-token>"
Then register the server manually with a bearer header — per-client commands in MCP only and MCP.md.
Note: never commit the PAT or paste it into config files — reference it only through the
TTAI_PATenvironment variable.
Which setup fits you?
| Setup | Best for | What you get |
|---|---|---|
| Plugin (recommended) | Claude Code, Codex, Cursor | Skills + MCP, auto-configured in one install |
| Skills + MCP, manual | Copilot, Windsurf, Gemini CLI, other agents | Same capability, assembled in two steps |
| Skills only | Any Agent Skills client, no live tools needed | Workflow guidance; the agent advises but can't act |
| MCP only | Developers who want raw API tools | 27 tools; no workflow guidance |
Not sure? Use the plugin — it's the least setup. Per-client instructions below. To freeze a git tag, commit, or a single skill, see INSTALL.md.
Set up
One command, every agent
The fastest path. The plugins CLI
detects the coding agents on your machine — Claude Code, Cursor, Codex,
Grok Build, Kimi Code, GitHub Copilot CLI, VS Code — and installs the
skills plus the MCP server into all of them at once:
npx plugins add tough-tongue/toughtongue-skills
Restart your agent, then say "get me started with Tough Tongue AI". The
ttai-agent intelligence layer verifies the connection and routes you to the
right workflow. On the first tool call your client opens the browser OAuth
consent — approve once and you're connected.
This repo is also a standard Agent Plugin
(root plugin.json, skills/, mcp.json), so clients that load Agent
Plugins natively can point straight at it. Prefer your client's own plugin
system? Per-client instructions below.
Claude Code
The plugin bundles the skills and registers the Tough Tongue AI MCP server
(.mcp.json) in one install: no separate claude mcp add step needed.
On the first tool call, Claude Code opens a browser OAuth consent — approve
once and you're connected (re-authenticate anytime with /mcp).
Inside Claude Code:
/plugin marketplace add tough-tongue/toughtongue-skills
/plugin install toughtongue@toughtongue-skills
Or from the terminal:
claude plugin marketplace add tough-tongue/toughtongue-skills
claude plugin install toughtongue@toughtongue-skills
Then say "get me started with Tough Tongue AI" or call
ttai:list_organizations. ttai-agent verifies the connection, takes a
lightweight inventory, and selects the relevant workflow.
Skills are namespaced after install: invoke them as
/toughtongue:scenario-maker,
/toughtongue:session-analyst, or /toughtongue:browser-demo-builder;
or just describe the task and Claude picks the right skill automatically.
Upgrade — refresh the marketplace catalog, then move the installed pin to the latest version:
claude plugin marketplace update toughtongue-skills
claude plugin update toughtongue@toughtongue-skills
Then run /reload-plugins in your session to apply.
Local development / testing — load the plugin without installing:
claude --plugin-dir /path/to/toughtongue-skills
# after edits, run /reload-plugins inside the session
Codex
The plugin bundles the skills and registers the Tough Tongue AI MCP server
(.mcp.json) in one install:
codex plugin marketplace add tough-tongue/toughtongue-skills
codex plugin add toughtongue@toughtongue
Then restart Codex and start a new thread. Codex detects the server's OAuth
support and prompts you to log in (or run codex mcp login ttai). Say "get
me started with Tough Tongue AI" to verify the setup and start your first
workflow.
Upgrade — both steps are needed; the first refreshes the marketplace snapshot, the second re-pins the installed plugin to it:
codex plugin marketplace upgrade toughtongue
codex plugin add toughtongue@toughtongue
Local development / testing — register the checkout as a local marketplace:
codex plugin marketplace add /path/to/toughtongue-skills
codex plugin add toughtongue@toughtongue
Cursor
In Cursor, go to Settings > Plugins > Team Marketplaces > Add Marketplace >
Import from Repo, point it at
https://github.com/tough-tongue/toughtongue-skills, then install
toughtongue.
Or assemble it manually in two steps:
-
Install the skills:
npx skills add tough-tongue/toughtongue-skills -
Add the MCP server: Install in Cursor — one click adds the server; Cursor prompts for OAuth consent on first use. Or add it manually via "Cursor Settings" > "MCP" (config JSON in MCP.md).
Re-import the marketplace from Settings > Plugins > Team Marketplaces.
If you installed the skills via the CLI, refresh them with
npx skills update.
Copilot / Windsurf / Gemini CLI / other agents
No plugin for these yet — install the skills and the MCP server as two steps:
1. Install the skills. Works with any Agent Skills-compatible client:
npx skills add tough-tongue/toughtongue-skills
The CLI prompts you to pick which skills to install and which agents to configure. To install everything non-interactively:
npx skills add tough-tongue/toughtongue-skills --all
Update existing skills later with:
npx skills update
2. Add the MCP server. Point your client at the hosted server — the general shape is:
{
"mcpServers": {
"ttai": {
"url": "https://api.toughtongueai.com/api/public/mcp"
}
}
}
Clients with OAuth support prompt for consent on first use. For clients (or
headless setups) that need a bearer token instead, add
"headers": { "Authorization": "Bearer ${TTAI_PAT}" } with the PAT from
Prerequisites. Exact config per client (Copilot/VS Code,
Windsurf, Gemini CLI) is in MCP.md.
Stdio-only clients (Claude Desktop, Zed, older VS Code): bridge to the hosted server with mcp-remote — see MCP.md.
Skills only
Want the workflow guidance without connecting your account?
npx skills add tough-tongue/toughtongue-skills
The agent can advise on scenario design, evaluation rubrics, and coaching patterns — but it can't create or modify anything in Tough Tongue AI. Add the MCP server later (step 2 above) when you want action.
MCP only
If you only want the tools (no skills) — OAuth flow starts on first use:
# Codex
codex mcp add ttai --url https://api.toughtongueai.com/api/public/mcp
codex mcp login ttai
# Claude Code
claude mcp add --transport http ttai https://api.toughtongueai.com/api/public/mcp
# then run /mcp in a session to authenticate
Headless / CI (PAT bearer auth instead of OAuth):
# Codex
codex mcp add ttai --url https://api.toughtongueai.com/api/public/mcp \
--bearer-token-env-var TTAI_PAT
# Claude Code
claude mcp add --transport http ttai https://api.toughtongueai.com/api/public/mcp \
--header "Authorization: Bearer ${TTAI_PAT}"
More clients in MCP.md.
Verify your setup
Ask your agent:
Call the ttai MCP tool list_organizations and show me the result.
Then list my scenarios.
You should see two things:
- The agent reaches your Tough Tongue AI account and returns real data — the MCP connection works.
- The agent reasons in Tough Tongue AI terms — scenarios, sessions, rubrics, report cards — the skills are loaded.
On a skills-only setup, verify with "What can I do with Tough Tongue AI?" — the agent should describe the workflows but won't be able to call tools.
What you can do
Coding agents are where work happens now. These journeys show Tough Tongue AI composing with the other tools already connected to your agent: copy any prompt to start.
1. Practice this sales call
A sales manager spots an AE struggling with pricing objections in real calls.
Pull the last 3 calls from Gong where we lost on pricing. Create a Tough Tongue AI scenario to practice handling that objection, using our positioning doc from Notion. Give me the shareable practice link.
Gong MCP (search_calls / list_calls → get_call_transcript) + Notion MCP
→ scenario-maker builds a sales roleplay from the real objections →
create_scenario → shareable practice link.
2. How is my team doing?
A VP of Sales wants the team's skill gaps, not raw transcripts.
For the "Enterprise Discovery Call" scenario, pull the last 50 sessions. What are the top 5 improvement areas? Build me a 3-slide deck.
session-analyst → list_sessions (scores, strengths, weaknesses per
session) → aggregates report-card topics and weakness themes → slides MCP for
the deck.
3. Refine from real conversations
A CS manager notices low scores on the onboarding scenario.
Pull the 5 lowest-scoring sessions for our onboarding scenario, figure out what went wrong, and fix the scenario.
list_sessions (sorted by score) → get_sessions_batch (full transcripts +
evaluations) → scenario-maker diagnoses the root cause → surgical
update_scenario: live for the next session.
4. Prep me for this meeting
A sales rep has a discovery call in 30 minutes.
I have a call with Sarah Chen from Acme Corp in 30 minutes. Create a quick practice scenario so I can rehearse.
Calendar MCP + web search for attendee/company context → scenario-maker
→ create_scenario → start practicing in minutes.
5. Automated post-call coaching
An engineering team wires coaching into their call pipeline.
Every time a call ends in Gong, analyze the transcript and email the rep a coaching report.
Webhook script → create_session (ingest transcript against a coaching
scenario) + post_process_session → poll get_sessions_batch until analysis
completes → email MCP sends the report. Full recipe in
session-analyst's report templates.
MCP Server
The plugin registers Tough Tongue AI's hosted MCP server at
https://api.toughtongueai.com/api/public/mcp (Streamable HTTP, OAuth 2.1
with dynamic client registration; PAT bearer auth for headless setups).
There is nothing to install and no local process to run. It exposes 27 tools
over the public API: scenarios (create, update, generate, access tokens),
sessions (list with evaluations, single and batch fetch, ingest,
post-process), analytics and organizations, SIP phone calls, meeting bots,
and collections.
See MCP.md for the full tool catalog, per-client setup (Claude Code, Codex, Cursor, Copilot, Windsurf, Gemini CLI), and troubleshooting.
The same OAuth flow powers the web connectors. In claude.ai, add a custom connector (Settings > Connectors) pointing at the server URL with the Client ID and Secret left empty. In ChatGPT (Business/Enterprise/Edu), enable developer mode and create a custom MCP app with OAuth. Full steps for both are in MCP.md.
Troubleshooting
- Fewer than 27 ttai tools listed: your agent trimmed or cached tool discovery. Start a fresh thread; if it persists, remove and re-add the MCP server.
- 401 / authentication errors: the OAuth login hasn't completed for this
client. Claude Code: run
/mcpand authenticate in the browser. Codex:codex mcp login ttai. Cursor: Cursor Settings > MCP > log in on the ttai server. If you're on a manual PAT config instead, checkTTAI_PATis visible to the agent process (re-export,launchctl setenvon macOS, fully restart the app). - Skills installed but the agent can't do anything: skills are guidance only — the agent also needs the MCP server for live actions. See Which setup fits you? and add the MCP server for your client.
- Using claude.ai or ChatGPT web?: same OAuth flow, via custom connectors. See the web connector sections in MCP.md.
- Scenario edits not taking effect in a running call: scenario changes apply to new sessions only; sessions compile their prompt at start.
If /plugin install fails or claude plugin list shows stale entries, do a
clean reinstall — run these in order in any Claude Code session:
/plugin marketplace remove toughtongue-skills/plugin marketplace add tough-tongue/toughtongue-skills/plugin marketplace update toughtongue-skills/plugin install toughtongue@toughtongue-skills
Step 3 forces Claude Code to re-read the marketplace manifest. After step 4,
claude plugin list should show one toughtongue@toughtongue-skills entry.
Repository structure
On-disk layout. How to pin a plugin, skill, or git ref: INSTALL.md.
toughtongue-skills/
├── plugin.json # Agent Plugins 1.0.0 manifest (agent-plugins.org)
├── mcp.json # Agent Plugins MCP config (streamable-http; no credentials)
├── .plugin/ # Marketplace entry for the `npx plugins` CLI
├── .claude-plugin/ # Claude Code plugin + marketplace manifests
├── .codex-plugin/ # Codex plugin manifest
├── .cursor-plugin/ # Cursor plugin manifest
├── .agents/plugins/ # Codex plugin-marketplace entry
├── .mcp.json # Claude-native MCP server registration (OAuth; no credentials)
├── MCP.md # MCP server docs: setup per client, tool catalog
├── skill-evals/ # Evaluation scenarios per skill
└── skills/ # Each: SKILL.md (+ kb/ / features/ or references/) + agents/openai.yaml
├── ttai-agent/ # Grand map: kb (entities, recipes) + features/mcp
├── scenario-maker/ # Create / edit / refine (loads ttai-agent)
├── session-analyst/ # Report templates
└── browser-demo-builder/ # Deterministic browser demo steps: format, selectors, example
Related
- Sign up · Developer portal / PAT · Platform docs · llms-full.txt (AI-readable API reference)
- Privacy policy ·
Terms of service — the canonical
legal URLs for Tough Tongue AI, required when submitting the MCP server to
the Claude Connectors Directory or a plugin marketplace. Note the paths:
/privacy-policy/and/terms/, not/privacyor/tos. - voice-ai-quickstart:
starter templates for building apps on Tough Tongue AI (Next.js, Flask,
co-navigation demo, scenario-as-code CLI) and the
toughtongue-aiintegration skill for developers embedding the platform.
License
MIT
Signals
- GitHub stars
- 7
- Last commit
- Sep 2026
Advanced
- Delivery
- mcp MCP server → your ahel gateway (mcp.ahel.ai) → every connected AI client.
- Catalog kind
- mcp-server
- Gateway key
com-toughtongueai-mcp- Source
- github.com/tough-tongue/toughtongue-skills
- Hosted endpoint
https://api.toughtongueai.com/api/public/mcp