Server definition
- Hash
- sha256:602486c8834b3b1fe1dad73a0bc9c6dfccdb43ee83237dbe443583135fce5900
- What it is
- What a remote MCP server returned when asked what it offers: 15 tools
The blob, as servednamed by its sha256
{
"instructions": "getcleed finds B2B prospects showing buying signals on LinkedIn and drafts the outreach.\n\nStart with get_pipeline_stats for the lay of the land, list_signals to see what this account treats as a buying signal, and get_icp for who it targets. list_prospects and get_prospect read the pipeline; every signal carries the verbatim quote from the post it came from, so quote that rather than paraphrasing.\n\nTo grow the pipeline: find_leads_from_signals searches recent LinkedIn posts on the account's own signal topics and returns ICP-matching people (nothing is saved until import_sourced_leads), add_leads_from_urls saves specific profiles, and analyze_prospects detects signals on prospects that have none.\n\nsend_email and send_linkedin_message reach real people immediately and cannot be undone. Show the user the draft and get their agreement before calling them.",
"tools": [
{
"description": "Save LinkedIn profiles as prospects and enrich them (name, role, company, industry, location, language). Skips anyone already saved. Counts against the import quota.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"linkedinUrls": {
"description": "LinkedIn profile URLs",
"items": {
"type": "string"
},
"type": "array"
},
"listId": {
"description": "Optional list to add them to (see get_icp for list ids)",
"type": "string"
}
},
"required": [
"linkedinUrls"
],
"type": "object"
},
"name": "add_leads_from_urls",
"outputSchema": null
},
{
"description": "Run the signal pipeline on prospects: enrich anyone missing company data, read their recent LinkedIn activity, and detect buying signals. Every signal kept must quote its source verbatim. Counts against the monthly analysis quota. Slow: expect up to a few minutes.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"limit": {
"default": 10,
"description": "Cap when prospectIds is omitted",
"type": "integer"
},
"prospectIds": {
"description": "Which prospects to analyze; omit to take those with no signals yet",
"items": {
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"name": "analyze_prospects",
"outputSchema": null
},
{
"description": "Teach the account a new buying signal to look for, described in plain language (for example \"people complaining their onboarding takes too long\"). Future analyses and sourcing will use it.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"detects": {
"description": "What to look for, in plain language",
"type": "string"
},
"exampleDetail": {
"type": "string"
},
"exampleTitle": {
"type": "string"
},
"name": {
"description": "Short display name",
"type": "string"
}
},
"required": [
"name",
"detects"
],
"type": "object"
},
"name": "create_custom_signal",
"outputSchema": null
},
{
"description": "Write a personalised email for a prospect, built from their detected signals, in their language. Saves the draft on the prospect and returns it. Does not send.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"language": {
"enum": [
"english",
"french"
],
"type": "string"
},
"linkedinUrl": {
"type": "string"
},
"prospectId": {
"type": "string"
},
"regenerate": {
"default": false,
"description": "Ignore any cached draft",
"type": "boolean"
},
"signalIndex": {
"default": 0,
"description": "Which signal to lead with",
"type": "integer"
}
},
"type": "object"
},
"name": "draft_email",
"outputSchema": null
},
{
"description": "Write a short LinkedIn connection note for a prospect from their detected signals, in their language. Saves the draft and returns it. Does not send.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"language": {
"enum": [
"english",
"french"
],
"type": "string"
},
"linkedinUrl": {
"type": "string"
},
"prospectId": {
"type": "string"
},
"regenerate": {
"default": false,
"type": "boolean"
}
},
"type": "object"
},
"name": "draft_linkedin_message",
"outputSchema": null
},
{
"description": "Search recent LinkedIn posts on the topics of this account's own signal definitions, keep only posts a check can prove are on topic, and return the people who wrote, commented on or reacted to them, filtered against the ICP (role, industry, country) and ranked. Nothing is saved: pass the returned candidates to import_sourced_leads. Spends a little of the monthly sourcing budget.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"postsPerSignal": {
"default": 3,
"type": "integer"
},
"signalType": {
"description": "Which signal to source for; omit to use the first enabled one (see list_signals)",
"type": "string"
}
},
"type": "object"
},
"name": "find_leads_from_signals",
"outputSchema": null
},
{
"description": "The active ICP: target roles, industries, countries, company sizes, relevant keywords and any exclusions. This is what sourcing and scoring filter against.",
"inputSchema": {
"additionalProperties": false,
"properties": {},
"type": "object"
},
"name": "get_icp",
"outputSchema": null
},
{
"description": "How the pipeline stands: how many prospects, how many carry signals, enrichment state, how many have an email address, how many were contacted, what was added in the last 7 days, the most common signal types, and the remaining plan quota.",
"inputSchema": {
"additionalProperties": false,
"properties": {},
"type": "object"
},
"name": "get_pipeline_stats",
"outputSchema": null
},
{
"description": "Everything known about one prospect: role, company, location, language, every detected signal with the verbatim quote from its source and the LinkedIn URL it came from, any existing email or LinkedIn draft, and outreach state.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"linkedinUrl": {
"description": "Their LinkedIn profile URL, if the id is unknown",
"type": "string"
},
"prospectId": {
"description": "The prospect id from list_prospects",
"type": "string"
}
},
"type": "object"
},
"name": "get_prospect",
"outputSchema": null
},
{
"description": "Save candidates returned by find_leads_from_signals. They arrive already enriched and with the signal attached, including the verbatim quote from the post that surfaced them. Counts against the import quota.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"listId": {
"type": "string"
},
"signalType": {
"description": "The signalType returned by find_leads_from_signals",
"type": "string"
},
"tokens": {
"description": "The token values of the candidates to import",
"items": {
"type": "string"
},
"type": "array"
}
},
"required": [
"signalType",
"tokens"
],
"type": "object"
},
"name": "import_sourced_leads",
"outputSchema": null
},
{
"description": "Search the saved prospects in the account. Filter by company, industry, job title, country, signal type, minimum number of signals, whether an email address is known, enrichment state, or whether they have been contacted. Ordered by signal count, then most recently saved.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"company": {
"type": "string"
},
"country": {
"type": "string"
},
"enrichmentStatus": {
"enum": [
"pending",
"enriched",
"failed"
],
"type": "string"
},
"hasEmail": {
"type": "boolean"
},
"industry": {
"type": "string"
},
"limit": {
"default": 20,
"description": "How many to return (max 50)",
"type": "integer"
},
"minSignals": {
"description": "Only prospects with at least this many signals",
"type": "integer"
},
"notContacted": {
"description": "Only prospects with no email sent yet",
"type": "boolean"
},
"offset": {
"default": 0,
"type": "integer"
},
"search": {
"description": "Free text matched against first name, last name, company and title",
"type": "string"
},
"signalType": {
"description": "Only prospects carrying a signal of this type (see list_signals)",
"type": "string"
},
"title": {
"description": "Job title contains this text",
"type": "string"
}
},
"type": "object"
},
"name": "list_prospects",
"outputSchema": null
},
{
"description": "The buying signals this account looks for: the predefined ones and the custom ones, each with the definition used to detect it and whether it is enabled. Use the returned type values with list_prospects and find_leads_from_signals.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"enabledOnly": {
"default": true,
"type": "boolean"
}
},
"type": "object"
},
"name": "list_signals",
"outputSchema": null
},
{
"description": "Record that a prospect was emailed outside getcleed, so reporting and follow-ups stay correct.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"linkedinUrl": {
"type": "string"
},
"prospectId": {
"type": "string"
}
},
"type": "object"
},
"name": "mark_email_sent",
"outputSchema": null
},
{
"description": "Send an email to a prospect from the connected mailbox. This reaches a real person immediately and cannot be undone. Pass the subject and body you want sent, or omit them to send the saved draft. Requires a mailbox connected in getcleed under Integrations.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"body": {
"description": "Omit to use the saved draft",
"type": "string"
},
"linkedinUrl": {
"type": "string"
},
"prospectId": {
"type": "string"
},
"subject": {
"description": "Omit to use the saved draft",
"type": "string"
}
},
"type": "object"
},
"name": "send_email",
"outputSchema": null
},
{
"description": "Send a LinkedIn connection request with a note to a prospect from the connected LinkedIn account. This reaches a real person immediately and cannot be undone. Pass the note you want sent, or omit it to use the saved draft. Requires LinkedIn connected in getcleed under Integrations.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"linkedinUrl": {
"type": "string"
},
"message": {
"description": "The note, max 300 characters. Omit to use the saved draft",
"type": "string"
},
"prospectId": {
"type": "string"
}
},
"type": "object"
},
"name": "send_linkedin_message",
"outputSchema": null
}
]
}Verify it yourself
curl -s https://api.teppi.xyz/v1/evidence/sha256:602486c8834b3b1fe1dad73a0bc9c6dfccdb43ee83237dbe443583135fce5900 | sha256sum