
Starlecta MCP server
Which MCP servers are Starlecta's own, from the official registry and from asking its own domain, whether they answer, and what they offer. A program checked each of these, nobody copied them from a product page.
read 2026-10-30
- Registry namecom.starlecta/influencer-toolsverified in the MCP registry
The registry name sits under starlecta.com. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.
- Stateanswerschecked 2026-10-30
- Tools5
- Server calls itselfstarlecta
- Server version1.0.0
- Protocol version2025-06-18
On 2026-10-30 the server answered initialize and tools/list without a sign-in. First answer in 241 ms.
- Whether its tools do the product's job has not been judged yet.
- Checked on 4 of the 7 days it takes to judge reliability.
Once connected
- Parameters are untyped or undescribed in 2 of 7 tools: check arguments before calling.
Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.
- INITE MCP scoreafter a weeka score needs 7 daily checks: 4 so far
- Answeredmeasuring4 of the 7 daily checks it takes to print a share
- Median first answer735 ms
- Space in an agent's context≈ 971 tokensthe definitions of all its tools (7), which an agent carries on every turn
- Tool definitionsA · 95 of 100
- Typed results0 of 7 toolsdeclared outputSchema: results come typed, read once
- Parameters without a description: in 2 of 7
What an agent can do with it
- not sure · find Instagram influencers by niche, city and audience
- not sure · compare influencer engagement and follower authenticity
- not sure · check which influencers have posted about which brands
Each of the product's use cases, put to Jev against this server's tool list: can an agent do it with these tools?
Worth a look
None of the five warning signs in these definitions.
A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →
lookup_influencerPublic card of one Instagram influencer Starlecta tracks: tier, category, rounded followers and the measured engagement rate with its date. Status is open, tracked or not_listed.
compare_influencersTwo influencers side by side on the same method and dates: followers, engagement rate and an engagement band.
search_influencersCount of matching influencers and up to two open cards. Filters: category code, tier (nano, micro, macro, mega), follower bounds, measured engagement only.
ai_search_influencersOne sentence in Turkish or English (2 to 200 characters), read as filters and niche words. Returns the count, up to two open cards with a match share and the niches that matched.
trend_cloudWhat influencers share in the last 7 days: rising hashtags with post counts, and the most shared products, platforms and brands with share counts. Aggregate counts only; no key needed.
How to connect
Add the server to your MCP client config. Claude Desktop, Cursor and most other clients read this shape:
{
"mcpServers": {
"influencer-tools": {
"type": "http",
"url": "https://starlecta.com/mcp"
}
}
}Add it
Claude Code, in a terminal
claude mcp add --transport http starlecta https://starlecta.com/mcpclaude.ai, ChatGPT and other clients: add https://starlecta.com/mcp as a custom connector in the settings.
Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.
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