tif-score-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| TIF_MODEL | No | The Claude model to use for scoring and diagnosis | claude-sonnet-4-6 |
| ANTHROPIC_API_KEY | Yes | Your Anthropic API key used for making Claude API calls |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| score_conversationA | Analyze a call transcript and extract structured business intelligence: intent, sentiment, urgency, objections, outcome, topics, missed-opportunity/follow-up flags, revenue signal, churn risk, and a plain-English summary. |
| get_lead_scoreA | Score a call transcript 0-100 and classify it hot/warm/cold. Internally runs the same analysis as score_conversation, then applies a point-based weighting to the resulting signals. |
| diagnose_workflow_errorA | Stateless diagnosis of an n8n workflow error: given the workflow JSON and error message, returns a root cause, a minimal proposed fix (or an honest 'not fixable by a workflow edit'), and a confidence level. Does not verify, deploy, or fetch anything live — pair with human or separate review before applying fixedWorkflow. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
get_lead_score and score_conversation both analyze call transcripts and clearly overlap — get_lead_score even notes it runs the same analysis as score_conversation. This creates real ambiguity about which to call. diagnose_workflow_error is completely distinct, but the two scoring tools blur boundaries significantly.
Tools use a consistent verb_noun pattern (get_lead_score, diagnose_workflow_error, score_conversation) with snake_case throughout. The naming styles are readable and consistent, though the verbs are somewhat varied (get, diagnose, score). No mixing of case conventions or chaotic patterns.
Three tools is at the thin end but not necessarily inappropriate. However, two of the three tools (get_lead_score and score_conversation) perform overlapping transcript analysis, making the actual distinct tool surface effectively two tools. The scope is unclear — the server mixes transcript scoring with completely unrelated n8n workflow diagnosis, suggesting no coherent singular purpose.
The transcript-analysis side lacks balance: it covers extraction and scoring but has no update, correction, or batch-processing capability. The n8n workflow tool appears to be an orphan — a single diagnostic tool with no companion tools for related functionality. The two unrelated domains each feel incomplete, and the overall surface has no clear lifecycle coverage.