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Glama
dheerajjha

blind-mcp

by dheerajjha

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
BLIND_COOKIENoOptional session cookie header for Blind. Copy from a logged-in browser request. Off by default.
BLIND_MCP_CACHE_DIRNoDirectory for on-disk response caching.
BLIND_MCP_CACHE_TTLNoCache time-to-live in seconds (default 6 hours).
BLIND_MCP_USER_AGENTNoThe User-Agent header sent with requests.
BLIND_MCP_MIN_INTERVALNoMinimum interval between requests in seconds (default ~1.5s).

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

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
company_topicsA

List the discussion topics Blind itself suggests for a company.

These are the highest-signal entry points -- e.g. Roku exposes india, wlb, culture, layoffs, interview, rsu. Use one as the topic for company_posts.

company_postsA

List posts about a company, optionally narrowed to one topic.

topic accepts a bare keyword from company_topics (e.g. "india", "wlb").

read_postA

Read one Blind post in full.

Returns the body, Blind's own AI summary of the comment thread, and the comments with each commenter's employer -- which is how you weigh a claim (an answer from someone at the company differs from a passer-by).

findA

Find a company's posts about one keyword.

This is how you search Blind. The company topic path accepts any keyword, so find("Intuit", "maternity") returns exactly the maternity threads -- which paging the main listing will not surface, since they can be years deep. Prefer one distinctive noun ("maternity", "rto", "refresher"); vague words like "policy" match hundreds of loosely-related posts.

Returns no posts when nothing matches, rather than falling back to the generic listing, so an empty result is a real answer.

researchA

Answer a question about a company by pulling the most relevant threads.

Probes the distinctive words in the question against Blind's keyword-scoped company pages, merges the hits, then returns the best threads in full with Blind's own AI summary and the comments that actually address the question.

Ask naturally: "how many days in office in India", "what is the maternity leave policy", "do they require a PhD".

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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