College Scorecard MCP Server vs EngrAmo
A side-by-side look at the College Scorecard MCP Server and EngrAmo MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose College Scorecard MCP Server for education work as a local process; choose EngrAmo for education over a hosted endpoint. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose College Scorecard MCP Server when
- You need dedicated capabilities in the Education domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
SCORECARD_API_KEY. - You want tools like
scorecard_search_schools, scorecard_get_school, scorecard_compare_schools.
Choose EngrAmo when
- You need dedicated capabilities in the Education domain.
- You prefer a remote HTTP/SSE transport.
- You have the keys it needs:
ENGRAMO_API_URL, ENGRAMO_API_TOKEN. - You want tools like
activate_learning_path, add_card_to_learning, add_catalog_to_learning.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Education | Education |
| Quality signal | 57/100 · Good | 72/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Remote HTTP/SSE |
| Auth | API key required | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | SCORECARD_API_KEY | ENGRAMO_API_URLENGRAMO_API_TOKEN |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 2 |
| Directory activity | 2 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 9 | 29 |
| Full listing | View College Scorecard MCP Server | View EngrAmo |
Tools & capabilities
College Scorecard MCP Server tools 9
scorecard_search_schoolsSearch institutions by name, location, type, size, acceptance rate, and single-sex flags; sort by supported API fields. Returns core identity and cost metrics.scorecard_get_schoolFull institutional profiles — costs, admissions, outcomes, aid, demographics, single-sex flags, and completion rates.scorecard_compare_schoolsNormalized side-by-side comparison of 2–5 schools on a named topic. Returns metric values, ordinal ranks, and a comparison summary.scorecard_get_programsField-of-study programs at one school: median 1-year earnings, cumulative Stafford/Grad PLUS debt, and IPEDS awards in the two pooled debt-cohort years.scorecard_search_programsFind programs by CIP and credential or keyword, retain degree identity, and rank earnings within each fetched school page.scorecard_get_earningsEarnings of federally aided undergraduate entrants working and not enrolled, regardless of completion: 6/8/10-year medians, 6/10-year P25/P75, and non-male/male 6-year medians.scorecard_value_analysisWorkflow tool: parallel-fetches cost, debt, repayment, and earnings data, then computes ROI metrics — debt-to-earnings ratio and net price to earnings ratio.scorecard_lookup_cipSearch 186 curated NCES CIP 2020 four-digit groups by code, keyword, or related program name. Served offline.scorecard_list_fieldsSearch the Scorecard field catalog by keyword. Returns matching field paths, descriptions, data types, and sort support. Use before passing custom `fields` parameters.
EngrAmo tools 29
activate_learning_pathActivate a learning path so its catalogs are included in daily reviews.add_card_to_learningAdd a single card to the learning queue. It will appear in due reviews. A card_id that doesn't exist is reported as "Not found"; one that belongs to another user is reported as a permission error (the API may also report a missing id that way).add_catalog_to_learningAdd all cards in a catalog to the learning queue at once.add_catalog_to_learning_pathAdd a catalog to a learning path so its cards become part of the path. Idempotent: adding a catalog that is already in the path succeeds (no error). A missing path or catalog returns Not found.create_learning_pathCreate a new learning path. It starts empty — use add_catalog_to_learning_path (or pass `catalog_ids` here) to populate it with catalogs. Passing `catalog_ids` adds each one in its own request right after the path is created (non-atomic): the path is never rolled back if a catalog fails to add, and the response then includes `catalogs_added`/`catalogs_failed` so failed ids can be retried.deactivate_learning_pathDeactivate a learning path so its catalogs are excluded from daily reviews.delete_cardDelete a flashcard from a catalog. If the card has learning progress it is archived (it stays in get_due_cards/get_all_learning_cards and remains reviewable, but get_card/update_card then report it as Not found); otherwise hard-deleted. A card_id that doesn't exist, or a catalog_id the card is not in, is reported as "Not found" and nothing is deleted; a card that belongs to another user is reported as a permission error (the API may also report a missing id that way).delete_catalogDelete a catalog. It is archived (not hard-deleted) if it has cards, a cover image, or is in an active learning path; otherwise it is hard-deleted. There is no restore/unarchive tool. Cards also in another live catalog are unaffected (they only lose this membership); cards only in this catalog stay reachable by id via get_card (showing `catalogs: []`) only until backend cleanup archives them; they disappear from search and list_cards immediately, and once archived get_card/update_card report them as Not found (cards with learning progress still appear in get_due_cards). To keep them, move them to another catalog with update_card (catalog_ids) BEFORE deleting. Catalog quota decrements automatically.generate_cardCreate a single styled flashcard. Pass catalog_id to add to an existing catalog; omit for the default catalog. For language-learning cards: translate face.text yourself and set back.text before calling; build a word-level dictionary (word → translation map) yourself and set face.dictionary. rich_text spans (IMPORTANT rules): ALWAYS set face.text and back.text to the full plain sentence — it is the ground truth. Each span's text must be a VERBATIM continuous segment of the original text — never add separator characters, markers, or ANY characters not present in the original sentence. Spans must partition face.text with no gaps; their concatenation must equal face.text exactly. The server validates this and discards richText if spans disagree with text. Styling goes under a nested `style` object on the span, never as flat fields, e.g. {"text":"gracias.","style":{"bold":true,"fontColor":"#27AE60"}}. Use fontFamily='monospace' for code, bold=true for key terms, fontColor='#E74C3C' for warnings, '#27AE60' for correct answers. If no styling needed, omit rich_text entirely and just set text.generate_cardsAdd multiple flashcards to an EXISTING catalog in one batch. Use this instead of calling generate_card N times. WARNING: cards are created one at a time — if one fails, previously created cards in this batch are NOT rolled back. Use generate_catalog_with_cards for atomic creation. For language-learning cards: translate each face.text yourself and set back.text; build a word-level dictionary (word → translation map) yourself and set face.dictionary on each card. rich_text spans (IMPORTANT rules): ALWAYS set face.text and back.text to the full plain sentence — it is the ground truth. Each span's text must be a VERBATIM continuous segment of the original text — never add separator characters, markers, or ANY characters not present in the original sentence. Spans must partition face.text with no gaps; their concatenation must equal face.text exactly. The server validates this and discards richText if spans disagree with text. Styling goes under a nested `style` object on the span, e.g. {"text":"gracias.","style":{"bold":true,"fontColor":"#27AE60"}}. At most 200 cards per call; split larger sets into several calls.generate_catalog_with_cardsCreate a new catalog together with all its flashcards in one atomic call. More efficient than creating cards one by one. For language-learning cards: translate each face.text yourself and set back.text; build a word-level dictionary (word → translation map) yourself and set face.dictionary on each card. rich_text spans (IMPORTANT rules): ALWAYS set face.text and back.text to the full plain sentence — it is the ground truth. Each span's text must be a VERBATIM continuous segment of the original text — never add separator characters, markers, or ANY characters not present in the original sentence. Spans must partition face.text with no gaps; their concatenation must equal face.text exactly. The server validates this and discards richText if spans disagree with text. Styling goes under a nested `style` object on the span, e.g. {"text":"gracias.","style":{"bold":true,"fontColor":"#27AE60"}}. The returned catalog's cardCount reflects the cards created in this call. At most 200 cards per call; split larger sets into several calls.get_all_learning_cardsGet all cards currently in the learning queue (due and future), with pagination. Returns at most 50 items per call; pass the returned `cursor` back to fetch the next page (`cursor: null` means this is the last page). A returned card may be archived (deleted after learning started): it stays reviewable here, but get_card/update_card report it as Not found.- +17 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
College Scorecard MCP Server
{
"mcpServers": {
"college-scorecard-mcp-server": {
"command": "npx",
"args": [
"-y",
"@cyanheads/college-scorecard-mcp-server"
],
"env": {
"SCORECARD_API_KEY": "YOUR_SCORECARD_API_KEY_HERE"
}
}
}
}
EngrAmo
{
"mcpServers": {
"engramo": {
"command": "npx",
"args": [
"-y",
"@engramo/mcp"
],
"env": {
"ENGRAMO_API_URL": "YOUR_ENGRAMO_API_URL_HERE",
"ENGRAMO_API_TOKEN": "YOUR_ENGRAMO_API_TOKEN_HERE"
}
}
}
}
Frequently asked questions
College Scorecard MCP Server is categorized under Education and uses a local stdio subprocess. EngrAmo belongs to Education and uses a remote HTTP/SSE transport. Pick College Scorecard MCP Server for education work and EngrAmo for education.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
College Scorecard MCP Server has no declared pricing — check the project's own site. Auth: api key required. EngrAmo has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add college-scorecard-mcp-server and engramo as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, College Scorecard MCP Server has a quality signal of 57/100 (Good) with 2 views, 0 installs and 1 GitHub stars. EngrAmo has 72/100 (Great) with 1 views, 0 installs and 2 GitHub stars.